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Koch E, Kämpe A, Alver M, Sigurðarson S, Einarsson G, Partanen J, Smith RL, Jaholkowski P, Taipale H, Lähteenvuo M, Steen NE, Smeland OB, Djurovic S, Molden E, Sigurdsson E, Stefánsson H, Stefánsson K, Palotie A, Milani L, O'Connell KS, Andreassen OA. Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study. Neuropsychopharmacology 2024; 49:1113-1119. [PMID: 38184734 PMCID: PMC11109158 DOI: 10.1038/s41386-023-01792-0] [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: 08/29/2023] [Revised: 11/10/2023] [Accepted: 12/19/2023] [Indexed: 01/08/2024]
Abstract
Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.
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Affiliation(s)
- Elise Koch
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Anders Kämpe
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Maris Alver
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | | | - Juulia Partanen
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Robert L Smith
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
| | - Piotr Jaholkowski
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Heidi Taipale
- Niuvanniemi Hospital, Kuopio, Finland
- Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, Stockholm, Sweden
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | | | - Nils Eiel Steen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
- Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Engilbert Sigurdsson
- Faculty of Medicine, University of Iceland and Department of Psychiatry, Landspitali, National University Hospital, Reykjavík, Iceland
| | | | | | - Aarno Palotie
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Kevin S O'Connell
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway.
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2
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Koch E, Pardiñas AF, O'Connell KS, Selvaggi P, Camacho Collados J, Babic A, Marshall SE, Van der Eycken E, Angulo C, Lu Y, Sullivan PF, Dale AM, Molden E, Posthuma D, White N, Schubert A, Djurovic S, Heimer H, Stefánsson H, Stefánsson K, Werge T, Sønderby I, O'Donovan MC, Walters JTR, Milani L, Andreassen OA. How Real-World Data Can Facilitate the Development of Precision Medicine Treatment in Psychiatry. Biol Psychiatry 2024:S0006-3223(24)00003-9. [PMID: 38185234 DOI: 10.1016/j.biopsych.2024.01.001] [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: 08/08/2023] [Revised: 12/20/2023] [Accepted: 01/02/2024] [Indexed: 01/09/2024]
Abstract
Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.
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Affiliation(s)
- Elise Koch
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Antonio F Pardiñas
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Kevin S O'Connell
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pierluigi Selvaggi
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - José Camacho Collados
- CardiffNLP, School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
| | | | | | - Erik Van der Eycken
- Global Alliance of Mental Illness Advocacy Networks-Europe, Brussels, Belgium
| | - Cecilia Angulo
- Global Alliance of Mental Illness Advocacy Networks-Europe, Brussels, Belgium
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden; Departments of Genetics and Psychiatry, University of North Carolina, Chapel Hill, North Carolina
| | - Anders M Dale
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, California; Departments of Radiology, Psychiatry, and Neurosciences, University of California, San Diego, La Jolla, California
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Nathan White
- CorTechs Laboratories, Inc., San Diego, California
| | | | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; The Norwegian Centre for Mental Disorders Research Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Hakon Heimer
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Nordic Society of Human Genetics and Precision Medicine, Copenhagen, Denmark
| | | | | | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark; Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark; Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Ida Sønderby
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia; Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway.
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3
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Sun W, Jin T, Yang H, Li J, Tian Q, Gao J, Peng R, Zhang G, Zhang X. Alterations of serum neuropeptide levels and their relationship to cognitive impairment and psychopathology in male patients with chronic schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:3. [PMID: 38172494 PMCID: PMC10851704 DOI: 10.1038/s41537-023-00425-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 12/07/2023] [Indexed: 01/05/2024]
Abstract
Serum neuropeptide levels may be linked to schizophrenia (SCZ) pathogenesis. This study aims to examine the relation between five serum neuropeptide levels and the cognition of patients with treatment-resistant schizophrenia (TRS), chronic stable schizophrenia (CSS), and in healthy controls (HC). Three groups were assessed: 29 TRS and 48 CSS patients who were hospitalized in regional psychiatric hospitals, and 53 HC. After the above participants were enrolled, we examined the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the blood serum levels of α-melanocyte stimulating hormone (α-MSH), β-endorphin (BE), neurotensin (NT), oxytocin (OT) and substance.P (S.P). Psychiatric symptoms in patients with SCZ were assessed with the Positive and Negative Syndrome Scale. SCZ patients performed worse than HC in total score and all subscales of the RBANS. The levels of the above five serum neuropeptides were significantly higher in SCZ than in HC. The levels of OT and S.P were significantly higher in CSS than in TRS patients. The α-MSH levels in TRS patients were significantly and negatively correlated with the language scores of RBANS. However, the BE and NT levels in CSS patients were significantly and positively correlated with the visuospatial/constructional scores of RBANS. Moreover, the interaction effect of NT and BE levels was positively associated with the visuospatial/constructional scores of RBANS. Therefore, abnormally increased serum neuropeptide levels may be associated with the physiology of SCZ, and may cause cognitive impairment and psychiatric symptoms, especially in patients with TRS.
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Affiliation(s)
- Wenxi Sun
- Suzhou Medical College of Soochow University, Suzhou, 215031, Jiangsu, China
- Psychiatry Department of Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu, China
| | - Tingting Jin
- Psychiatry Department of Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu, China
| | - Haidong Yang
- Department of Psychiatry, The Fourth People's Hospital of Lianyungang, The Affiliated KangDa College of Nanjing Medical University, Lianyungang, 222003, PR China
| | - Jin Li
- Psychiatry Department of Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu, China
| | - Qing Tian
- Psychiatry Department of Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu, China
| | - Ju Gao
- Psychiatry Department of Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu, China
| | - Ruijie Peng
- Suzhou Medical College of Soochow University, Suzhou, 215031, Jiangsu, China
| | - Guangya Zhang
- Psychiatry Department of Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu, China.
| | - Xiaobin Zhang
- Psychiatry Department of Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu, China.
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Mohamed Saini S, Bousman CA, Mancuso SG, Cropley V, Van Rheenen TE, Lenroot RK, Bruggemann J, Weickert CS, Weickert TW, Sundram S, Everall IP, Pantelis C. Genetic variation in glutamatergic genes moderates the effects of childhood adversity on brain volume and IQ in treatment-resistant schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:59. [PMID: 37709784 PMCID: PMC10502098 DOI: 10.1038/s41537-023-00381-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/20/2023] [Indexed: 09/16/2023]
Affiliation(s)
- Suriati Mohamed Saini
- Department of Psychiatry, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Cheras, Kuala Lumpur, Malaysia.
- Department of Psychiatry, Hospital Canselor Tuanku Muhriz, Jalan Yaacob Latif, Cheras, Kuala Lumpur, Malaysia.
| | - Chad A Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Alberta Children's Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Medical Genetics, Psychiatry, and Physiology and Pharmacology, The University of Calgary, Calgary, AB, Canada
| | - Serafino G Mancuso
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University, Melbourne, VIC, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University, Melbourne, VIC, Australia
| | - Rhoshel K Lenroot
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Department of Psychiatry and Behavioural Science, University of New Mexico, Albuquerque, NM, USA
| | - Jason Bruggemann
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Neuroscience Research Australia, Randwick, NSW, Australia
- Schizophrenia Research Institute, Sydney, NSW, Australia
| | - Cynthia S Weickert
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, NY, USA
- Schizophrenia Research Laboratory, Neuroscience Research Australia, NSW, Australia
| | - Thomas W Weickert
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, NY, USA
| | - Suresh Sundram
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC, Australia
- Monash Medical Centre, Monash Health, Clayton, VIC, Australia
| | - Ian P Everall
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Western Centre for Health Research & Education, Sunshine Hospital, Western Health, St Albans, VIC, 3021, Australia
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Diniz E, Fonseca L, Rocha D, Trevizol A, Cerqueira R, Ortiz B, Brunoni AR, Bressan R, Correll CU, Gadelha A. Treatment resistance in schizophrenia: a meta-analysis of prevalence and correlates. REVISTA BRASILEIRA DE PSIQUIATRIA (SAO PAULO, BRAZIL : 1999) 2023; 45:448-458. [PMID: 37718484 PMCID: PMC10894625 DOI: 10.47626/1516-4446-2023-3126] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/19/2023] [Indexed: 09/19/2023]
Abstract
OBJECTIVES To determine the prevalence and correlates of treatment-resistant schizophrenia (TRS) through a systematic review and meta-analysis. METHODS Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria, an electronic search was performed in PubMed and Embase through May 17, 2022. All study designs that assessed a minimum of 20 schizophrenia-spectrum patients and provided data on TRS prevalence or allowed its calculation were included. Estimates were produced using a random-effects model meta-analysis. RESULTS The TRS prevalence across 50 studies (n = 29,390) was 36.7% (95%CI 33.1-40.5, p < 0.0001). The prevalence ranged from 22% (95%CI 18.4-25.8) in first-episode to 39.5% (95%CI 32.2-47.0) in multiple-episode samples (Q = 18.27, p < 0.0001). Primary treatment resistance, defined as no response from the first episode, was 23.6% (95%CI 20.5-26.8) vs. 9.3% (95%CI 6.8-12.2) for later-onset/secondary (≥ 6 months after initial treatment response). Longer illness duration and recruitment from long-term hospitals or clozapine clinics were associated with higher prevalence estimates. In meta-regression analyses, older age and poor functioning predicted greater TRS. When including only studies with lower bias risk, the TRS prevalence was 28.4%. CONCLUSION Different study designs and recruitment strategies accounted for most of the observed heterogeneity in TRS prevalence rates. The results point to early-onset and later-onset TRS as two separate disease pathways requiring clinical attention.
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Affiliation(s)
- Elton Diniz
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Programa de Esquizofrenia, Departamento de Psiquiatria, UNIFESP, São Paulo, SP, Brazil
| | - Lais Fonseca
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Programa de Esquizofrenia, Departamento de Psiquiatria, UNIFESP, São Paulo, SP, Brazil
| | - Deyvis Rocha
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Programa de Esquizofrenia, Departamento de Psiquiatria, UNIFESP, São Paulo, SP, Brazil
| | - Alisson Trevizol
- Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Raphael Cerqueira
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Programa de Esquizofrenia, Departamento de Psiquiatria, UNIFESP, São Paulo, SP, Brazil
| | - Bruno Ortiz
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Programa de Esquizofrenia, Departamento de Psiquiatria, UNIFESP, São Paulo, SP, Brazil
| | - André R. Brunoni
- Serviço Interdisciplinar de Neuromodulação, Departamento de Psiquiatria, Instituto de Psiquiatria, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
- Laboratório de Neurociências, Departamento de Psiquiatria, Instituto de Psiquiatria, USP, São Paulo, SP, Brazil
| | - Rodrigo Bressan
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
| | - Christoph U. Correll
- Department of Psychiatry, The Zucker Hillside Hospital, New York, NY, USA
- Department of Psychiatry and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Ary Gadelha
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Programa de Esquizofrenia, Departamento de Psiquiatria, UNIFESP, São Paulo, SP, Brazil
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O'Connell KS, Koch E, Lenk HÇ, Akkouh IA, Hindley G, Jaholkowski P, Smith RL, Holen B, Shadrin AA, Frei O, Smeland OB, Steen NE, Dale AM, Molden E, Djurovic S, Andreassen OA. Polygenic overlap with body-mass index improves prediction of treatment-resistant schizophrenia. Psychiatry Res 2023; 325:115217. [PMID: 37146461 PMCID: PMC10788293 DOI: 10.1016/j.psychres.2023.115217] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 04/03/2023] [Accepted: 04/21/2023] [Indexed: 05/07/2023]
Abstract
Treatment resistant schizophrenia (TRS) is characterized by repeated treatment failure with antipsychotics. A recent genome-wide association study (GWAS) of TRS showed a polygenic architecture, but no significant loci were identified. Clozapine is shown to be the superior drug in terms of clinical effect in TRS; at the same time it has a serious side effect profile, including weight gain. Here, we sought to increase power for genetic discovery and improve polygenic prediction of TRS, by leveraging genetic overlap with Body Mass Index (BMI). We analysed GWAS summary statistics for TRS and BMI applying the conditional false discovery rate (cFDR) framework. We observed cross-trait polygenic enrichment for TRS conditioned on associations with BMI. Leveraging this cross-trait enrichment, we identified 2 novel loci for TRS at cFDR <0.01, suggesting a role of MAP2K1 and ZDBF2. Further, polygenic prediction based on the cFDR analysis explained more variance in TRS when compared to the standard TRS GWAS. These findings highlight putative molecular pathways which may distinguish TRS patients from treatment responsive patients. Moreover, these findings confirm that shared genetic mechanisms influence both TRS and BMI and provide new insights into the biological underpinnings of metabolic dysfunction and antipsychotic treatment.
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Affiliation(s)
- Kevin S O'Connell
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Elise Koch
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Hasan Çağın Lenk
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway; Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Ibrahim A Akkouh
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Guy Hindley
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, United Kingdom
| | - Piotr Jaholkowski
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Robert Løvsletten Smith
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
| | - Børge Holen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Alexey A Shadrin
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Center for Bioinformatics, Department of Informatics, University of Oslo, 0316 Oslo, Norway
| | - Olav B Smeland
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nils Eiel Steen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA; Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway; Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway.
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7
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Chen W, Gou M, Wang L, Li N, Li W, Tong J, Zhou Y, Xie T, Yu T, Feng W, Li Y, Chen S, Tian B, Tan S, Wang Z, Pan S, Luo X, Zhang P, Huang J, Tian L, Li CSR, Tan Y. Inflammatory disequilibrium and lateral ventricular enlargement in treatment-resistant schizophrenia. Eur Neuropsychopharmacol 2023; 72:18-29. [PMID: 37058967 DOI: 10.1016/j.euroneuro.2023.03.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/28/2023] [Accepted: 03/30/2023] [Indexed: 04/16/2023]
Abstract
Treatment-resistant schizophrenia (TRS) patient respond poorly to antipsychotics. Inflammatory imbalance involving pro- and anti-inflammatory cytokines may play an important role in the mechanism of antipsychotic-medication response. This study aimed to investigate immune imbalance and how the latter relates to clinical manifestations in patients with TRS. The level of net inflammation was estimated by evaluating the immune-inflammatory response system and compensatory immune-regulatory reflex system (IRS/CIRS) in 52 patients with TRS, 47 with non-TRS, and 56 sex and age matched healthy controls. The immune biomarkers mainly included macrophagic M1, T helper, Th-1, Th-2, Th-17, and T regulatory cytokines and receptors. Plasma cytokine levels were measured using enzyme-linked immunosorbent assay. Psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS). Subcortical volumes were quantified using a 3-T Prisma Magnetic Resonance Imaging scanner. The results showed that (1) patients with TRS were characterized by activated pro-inflammatory cytokines and relatively insufficient anti-inflammatory cytokines, with an elevated IRS/CIRS ratio indicating a new homeostatic immune setpoint; (2) IRS/CIRS ratio was positively correlated with larger lateral ventricle volume and higher PANSS score in patients with TRS. Our findings highlighted the inflammatory disequilibrium as a potential pathophysiological process of TRS.
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Affiliation(s)
- Wenjin Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Mengzhuang Gou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Leilei Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Na Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Xie
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Feng
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shujuan Pan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China.
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8
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Mawson ER, Morris BJ. A consideration of the increased risk of schizophrenia due to prenatal maternal stress, and the possible role of microglia. Prog Neuropsychopharmacol Biol Psychiatry 2023; 125:110773. [PMID: 37116354 DOI: 10.1016/j.pnpbp.2023.110773] [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: 10/31/2022] [Revised: 04/07/2023] [Accepted: 04/18/2023] [Indexed: 04/30/2023]
Abstract
Schizophrenia is caused by interaction of a combination of genetic and environmental factors. Of the latter, prenatal exposure to maternal stress is reportedly associated with elevated disease risk. The main orchestrators of inflammatory processes within the brain are microglia, and aberrant microglial activation/function has been proposed to contribute to the aetiology of schizophrenia. Here, we evaluate the epidemiological and preclinical evidence connecting prenatal stress to schizophrenia risk, and consider the possible mediating role of microglia in the prenatal stress-schizophrenia relationship. Epidemiological findings are rather consistent in supporting the association, albeit they are mitigated by effects of sex and gestational timing, while the evidence for microglial activation is more variable. Rodent models of prenatal stress generally report lasting effects on offspring neurobiology. However, many uncertainties remain as to the mechanisms underlying the influence of maternal stress on the developing foetal brain. Future studies should aim to characterise the exact processes mediating this aspect of schizophrenia risk, as well as focussing on how prenatal stress may interact with other risk factors.
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Affiliation(s)
- Eleanor R Mawson
- School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK
| | - Brian J Morris
- School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK.
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9
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Iasevoli F, D’Ambrosio L, Ciccarelli M, Barone A, Gaudieri V, Cocozza S, Pontillo G, Brunetti A, Cuocolo A, de Bartolomeis A, Pappatà S. Altered Patterns of Brain Glucose Metabolism Involve More Extensive and Discrete Cortical Areas in Treatment-resistant Schizophrenia Patients Compared to Responder Patients and Controls: Results From a Head-to-Head 2-[18F]-FDG-PET Study. Schizophr Bull 2023; 49:474-485. [PMID: 36268829 PMCID: PMC10016407 DOI: 10.1093/schbul/sbac147] [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] [Indexed: 01/10/2023]
Abstract
BACKGROUND AND HYPOTHESIS Treatment resistant schizophrenia (TRS) affects almost 30% of patients with schizophrenia and has been considered a different phenotype of the disease. In vivo characterization of brain metabolic patterns associated with treatment response could contribute to elucidate the neurobiological underpinnings of TRS. Here, we used 2-[18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) to provide the first head-to-head comparative analysis of cerebral glucose metabolism in TRS patients compared to schizophrenia responder patients (nTRS), and controls. Additionally, we investigated, for the first time, the differences between clozapine responders (Clz-R) and non-responders (Clz-nR). STUDY DESIGN 53 participants underwent FDG-PET studies (41 patients and 12 controls). Response to conventional antipsychotics and to clozapine was evaluated using a standardized prospective procedure based on PANSS score changes. Maps of relative brain glucose metabolism were processed for voxel-based analysis using Statistical Parametric Mapping software. STUDY RESULTS Restricted areas of significant bilateral relative hypometabolism in the superior frontal gyrus characterized TRS compared to nTRS. Moreover, reduced parietal and frontal metabolism was associated with high PANSS disorganization factor scores in TRS (P < .001 voxel level uncorrected, P < .05 cluster level FWE-corrected). Only TRS compared to controls showed significant bilateral prefrontal relative hypometabolism, more extensive in CLZ-nR than in CLZ-R (P < .05 voxel level FWE-corrected). Relative significant hypermetabolism was observed in the temporo-occipital regions in TRS compared to nTRS and controls. CONCLUSIONS These data indicate that, in TRS patients, altered metabolism involved discrete brain regions not found affected in nTRS, possibly indicating a more severe disrupted functional brain network associated with disorganization symptoms.
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Affiliation(s)
- Felice Iasevoli
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Luigi D’Ambrosio
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Annarita Barone
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Valeria Gaudieri
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Alberto Cuocolo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
- UNESCO Chair on Health Education and Sustainable Development - University of Naples Federico II, Naples, Italy
| | - Sabina Pappatà
- Institute of Biostructure and Bioimaging, National Research Council, Via T. De Amicis 95, 80145, Naples, Italy
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10
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Dopamine Dynamics and Neurobiology of Non-Response to Antipsychotics, Relevance for Treatment Resistant Schizophrenia: A Systematic Review and Critical Appraisal. Biomedicines 2023; 11:biomedicines11030895. [PMID: 36979877 PMCID: PMC10046109 DOI: 10.3390/biomedicines11030895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/08/2023] [Accepted: 03/12/2023] [Indexed: 03/17/2023] Open
Abstract
Treatment resistant schizophrenia (TRS) is characterized by a lack of, or suboptimal response to, antipsychotic agents. The biological underpinnings of this clinical condition are still scarcely understood. Since all antipsychotics block dopamine D2 receptors (D2R), dopamine-related mechanisms should be considered the main candidates in the neurobiology of antipsychotic non-response, although other neurotransmitter systems play a role. The aims of this review are: (i) to recapitulate and critically appraise the relevant literature on dopamine-related mechanisms of TRS; (ii) to discuss the methodological limitations of the studies so far conducted and delineate a theoretical framework on dopamine mechanisms of TRS; and (iii) to highlight future perspectives of research and unmet needs. Dopamine-related neurobiological mechanisms of TRS may be multiple and putatively subdivided into three biological points: (1) D2R-related, including increased D2R levels; increased density of D2Rs in the high-affinity state; aberrant D2R dimer or heteromer formation; imbalance between D2R short and long variants; extrastriatal D2Rs; (2) presynaptic dopamine, including low or normal dopamine synthesis and/or release compared to responder patients; and (3) exaggerated postsynaptic D2R-mediated neurotransmission. Future points to be addressed are: (i) a more neurobiologically-oriented phenotypic categorization of TRS; (ii) implementation of neurobiological studies by directly comparing treatment resistant vs. treatment responder patients; (iii) development of a reliable animal model of non-response to antipsychotics.
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11
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M Elsharkawy F, M Amin M, A Shamsel-Din H, Ibrahim W, Ibrahim AB, Sayed S. Self-Assembling Lecithin-Based Mixed Polymeric Micelles for Nose to Brain Delivery of Clozapine: In-vivo Assessment of Drug Efficacy via Radiobiological Evaluation. Int J Nanomedicine 2023; 18:1577-1595. [PMID: 37007986 PMCID: PMC10065422 DOI: 10.2147/ijn.s403707] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 03/14/2023] [Indexed: 03/28/2023] Open
Abstract
Purpose The research objective is to design intranasal brain targeted CLZ loaded lecithin based polymeric micelles (CLZ- LbPM) aiming to improve central systemic CLZ bioavailability. Methods In our study, intranasal CLZ loaded lecithin based polymeric micelles (CLZ- LbPM) were formulated using soya phosphatidyl choline (SPC) and sodium deoxycholate (SDC) with different CLZ:SPC:SDC ratios via thin film hydration technique aiming to enhance drug solubility, bioavailability and nose to brain targeting efficiency. Optimization of the prepared CLZ-LbPM using Design-Expert® software was achieved showing that M6 which composed of (CLZ:SPC: SDC) in respective ratios of 1:3:10 was selected as the optimized formula. The optimized formula was subjected to further evaluation tests as, Differential Scanning Calorimetry (DSC), TEM, in vitro release profile, ex vivo intranasal permeation and in vivo biodistribution. Results The optimized formula with the highest desirability exhibiting (0.845), small particle size (12.23±4.76 nm), Zeta potential of (-38 mV), percent entrapment efficiency of > 90% and percent drug loading of 6.47%. Ex vivo permeation test showed flux value of 27 μg/cm².h and the enhancement ratio was about 3 when compared to the drug suspension, without any histological alteration. The radioiodinated clozapine ([131I] iodo-CLZ) and radioiodinated optimized formula ([131I] iodo-CLZ-LbPM) were formulated in an excellent radioiodination yield more than 95%. In vivo biodistribution studies of [131I] iodo-CLZ-LbPM showed higher brain uptake (7.8%± 0.1%ID/g) for intranasal administration with rapid onset of action (at 0.25 h) than the intravenous formula. Its pharmacokinetic behavior showed relative bioavailability, direct transport percentage from nose to brain and drug targeting efficiency of 170.59%, 83.42% and 117% respectively. Conclusion The intranasal self-assembling lecithin based mixed polymeric micelles could be an encouraging way for CLZ brain targeting.
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Affiliation(s)
- Fatma M Elsharkawy
- Regulatory Affairs Department, Al Andalous for Pharmaceutical Industries, Giza, Egypt
| | - Maha M Amin
- Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Cairo University, Cairo, Egypt
| | - Hesham A Shamsel-Din
- Labeled Compounds Department, Hot Labs Center, Egyptian Atomic Energy Authority, Cairo, 13759, Egypt
| | - Walaa Ibrahim
- Labeled Compounds Department, Hot Labs Center, Egyptian Atomic Energy Authority, Cairo, 13759, Egypt
| | - Ahmed B Ibrahim
- Labeled Compounds Department, Hot Labs Center, Egyptian Atomic Energy Authority, Cairo, 13759, Egypt
| | - Sinar Sayed
- Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Cairo University, Cairo, Egypt
- Correspondence: Sinar Sayed, Faculty of Pharmacy, Cairo University, Kasr El-Aini, Cairo, 11562, Egypt, Tel +2 01010421543, Email
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12
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Funding research to understand mechanisms of commercialized antipsychotic drugs could transform the future of mental health therapeutics. Behav Brain Res 2023; 438:114214. [PMID: 36372241 DOI: 10.1016/j.bbr.2022.114214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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13
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Qubad M, Bittner RA. Second to none: rationale, timing, and clinical management of clozapine use in schizophrenia. Ther Adv Psychopharmacol 2023; 13:20451253231158152. [PMID: 36994117 PMCID: PMC10041648 DOI: 10.1177/20451253231158152] [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: 11/16/2022] [Accepted: 01/24/2023] [Indexed: 03/31/2023] Open
Abstract
Despite its enduring relevance as the single most effective and important evidence-based treatment for schizophrenia, underutilization of clozapine remains considerable. To a substantial degree, this is attributable to a reluctance of psychiatrists to offer clozapine due to its relatively large side-effect burden and the complexity of its use. This underscores the necessity for continued education regarding both the vital nature and the intricacies of clozapine treatment. This narrative review summarizes all clinically relevant areas of evidence, which support clozapine's wide-ranging superior efficacy - for treatment-resistant schizophrenia (TRS) and beyond - and make its safe use eminently feasible. Converging evidence indicates that TRS constitutes a distinct albeit heterogeneous subgroup of schizophrenias primarily responsive to clozapine. Most importantly, the predominantly early onset of treatment resistance and the considerable decline in response rates associated with its delayed initiation make clozapine an essential treatment option throughout the course of illness, beginning with the first psychotic episode. To maximize patients' benefits, systematic early recognition efforts based on stringent use of TRS criteria, a timely offer of clozapine, thorough side-effect screening and management as well as consistent use of therapeutic drug monitoring and established augmentation strategies for suboptimal responders are crucial. To minimize permanent all-cause discontinuation, re-challenges after neutropenia or myocarditis should be considered. Owing to clozapine's unique efficacy, comorbid conditions including substance use and most somatic disorders should not dissuade but rather encourage clinicians to consider clozapine. Moreover, treatment decisions need to be informed by the late onset of clozapine's full effects, which for reduced suicidality and mortality rates may not even be readily apparent. Overall, the singular extent of its efficacy combined with the high level of patient satisfaction continues to distinguish clozapine from all other available antipsychotics.
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Affiliation(s)
- Mishal Qubad
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
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14
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de Bartolomeis A, Ciccarelli M, Vellucci L, Fornaro M, Iasevoli F, Barone A. Update on novel antipsychotics and pharmacological strategies for treatment resistant schizophrenia. Expert Opin Pharmacother 2022; 23:2035-2052. [DOI: 10.1080/14656566.2022.2145884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Andrea de Bartolomeis
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science and Dentistry, University of Naples “Federico II”, Naples, Italy
| | - Mariateresa Ciccarelli
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science and Dentistry, University of Naples “Federico II”, Naples, Italy
| | - Licia Vellucci
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science and Dentistry, University of Naples “Federico II”, Naples, Italy
| | - Michele Fornaro
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science and Dentistry, University of Naples “Federico II”, Naples, Italy
| | - Felice Iasevoli
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science and Dentistry, University of Naples “Federico II”, Naples, Italy
| | - Annarita Barone
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science and Dentistry, University of Naples “Federico II”, Naples, Italy
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15
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Fonseca de Freitas D, Agbedjro D, Kadra-Scalzo G, Francis E, Ridler I, Pritchard M, Shetty H, Segev A, Casetta C, Smart SE, Morris A, Downs J, Christensen SR, Bak N, Kinon BJ, Stahl D, Hayes RD, MacCabe JH. Clinical correlates of early onset antipsychotic treatment resistance. J Psychopharmacol 2022; 36:1226-1233. [PMID: 36268751 PMCID: PMC9643817 DOI: 10.1177/02698811221132537] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND There is evidence of heterogeneity within treatment-resistant schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and others becoming treatment-resistant after an initial response period. These groups may have different aetiologies. AIM This study investigates sociodemographic and clinical correlates of early onset of TRS. METHOD Employing a retrospective cohort design, we do a secondary analysis of data from a cohort of people with TRS attending the South London and Maudsley. Regression analyses were conducted to identify the correlates of the length of treatment to TRS. Predictors included the following: gender, age, ethnicity, problems with positive symptoms, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics. RESULTS In a cohort of 164 people with TRS (60% were men), the median length of treatment to TRS was 3 years and 8 months. We observed no cut-off on the length of treatment until TRS presentation differentiating between early and late TRS (i.e. no bimodal distribution). Having mild to very severe problems with hallucinations and delusions at the treatment start was associated with earlier TRS (~19 months earlier). In sensitivity analyses, including only complete cases (subject to selection bias), treatment with a long-acting injectable antipsychotic was additionally associated with later TRS (~15 months later). CONCLUSION Our findings do not support a clear separation between early and late TRS but rather a continuum of the length of treatment before TRS onset. Having mild to very severe problems with positive symptoms at treatment start predicts earlier onset of TRS.
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Affiliation(s)
- Daniela Fonseca de Freitas
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
- Department of Psychiatry, University of
Oxford, Oxford, UK
| | - Deborah Agbedjro
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
| | | | - Emma Francis
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
- Division of Psychology and Language
Sciences, University College London, London, UK
| | - Isobel Ridler
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
| | - Megan Pritchard
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
- South London and Maudsley NHS
Foundation Trust, London, UK
- Norwich Medical School, University of
East Anglia, Norwich, UK
| | - Hitesh Shetty
- South London and Maudsley NHS
Foundation Trust, London, UK
| | - Aviv Segev
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
- Sackler Faculty of Medicine, Tel Aviv
University, Tel Aviv, Israel
- Shalvata Mental Health Center, Hod
Hasharon, Israel
| | - Cecilia Casetta
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
- Department of Health Sciences,
Università degli Studi di Milano, Milan, Italy
| | - Sophie E. Smart
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
- MRC Centre for Neuropsychiatric
Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Anna Morris
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
| | - Johnny Downs
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
- South London and Maudsley NHS
Foundation Trust, London, UK
| | | | | | - Bruce J. Kinon
- Lundbeck Pharmaceuticals LLC,
Deerfield, IL, USA
- Cyclerion Therapeutics, Cambridge,
MA, USA
| | - Daniel Stahl
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
| | - Richard D. Hayes
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
| | - James H. MacCabe
- Institute of Psychiatry, Psychology and
Neuroscience, King’s College London, London, UK
- South London and Maudsley NHS
Foundation Trust, London, UK
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16
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Shnayder NA, Khasanova AK, Strelnik AI, Al-Zamil M, Otmakhov AP, Neznanov NG, Shipulin GA, Petrova MM, Garganeeva NP, Nasyrova RF. Cytokine Imbalance as a Biomarker of Treatment-Resistant Schizophrenia. Int J Mol Sci 2022; 23:ijms231911324. [PMID: 36232626 PMCID: PMC9570417 DOI: 10.3390/ijms231911324] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 09/19/2022] [Accepted: 09/21/2022] [Indexed: 11/24/2022] Open
Abstract
Treatment-resistant schizophrenia (TRS) is an important and unresolved problem in biological and clinical psychiatry. Approximately 30% of cases of schizophrenia (Sch) are TRS, which may be due to the fact that some patients with TRS may suffer from pathogenetically “non-dopamine” Sch, in the development of which neuroinflammation is supposed to play an important role. The purpose of this narrative review is an attempt to summarize the data characterizing the patterns of production of pro-inflammatory and anti-inflammatory cytokines during the development of therapeutic resistance to APs and their pathogenetic and prognostic significance of cytokine imbalance as TRS biomarkers. This narrative review demonstrates that the problem of evaluating the contribution of pro-inflammatory and anti-inflammatory cytokines to maintaining or changing the cytokine balance can become a new key in unlocking the mystery of “non-dopamine” Sch and developing new therapeutic strategies for the treatment of TRS and psychosis in the setting of acute and chronic neuroinflammation. In addition, the inconsistency of the results of previous studies on the role of pro-inflammatory and anti-inflammatory cytokines indicates that the TRS biomarker, most likely, is not the serum level of one or more cytokines, but the cytokine balance. We have confirmed the hypothesis that cytokine imbalance is one of the most important TRS biomarkers. This hypothesis is partially supported by the variable response to immunomodulators in patients with TRS, which were prescribed without taking into account the cytokine balance of the relation between serum levels of the most important pro-inflammatory and anti-inflammatory cytokines for TRS.
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Affiliation(s)
- Natalia A. Shnayder
- Institute of Personalized Psychiatry and Neurology, Shared Core Facilities, V.M. Bekhterev National Medical Research Centre for Psychiatry and Neurology, 192019 Saint Petersburg, Russia
- Shared Core Facilities “Molecular and Cell Technologies”, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
- Correspondence: (N.A.S.); (R.F.N.); Tel.: +7-(812)-620-02-20-78-13 (N.A.S. & R.F.N.)
| | - Aiperi K. Khasanova
- Institute of Personalized Psychiatry and Neurology, Shared Core Facilities, V.M. Bekhterev National Medical Research Centre for Psychiatry and Neurology, 192019 Saint Petersburg, Russia
| | - Anna I. Strelnik
- International Centre for Education and Research in Neuropsychiatry, Samara State Medical University, 443016 Samara, Russia
- Department of Psychiatry, Narcology and Psychotherapy, Samara State Medical University, 443016 Samara, Russia
| | - Mustafa Al-Zamil
- Department of Physiotherapy, Faculty of Continuing Medical Education, Peoples’ Friendship University of Russia, 117198 Moscow, Russia
| | - Andrey P. Otmakhov
- Basic Department of Psychological and Social Support, St. Petersburg State Institute of Psychology and Social Work, 199178 Saint Petersburg, Russia
- St. Nikolay Psychiatric Hospital, 190121 Saint Petersburg, Russia
| | - Nikolay G. Neznanov
- Institute of Personalized Psychiatry and Neurology, Shared Core Facilities, V.M. Bekhterev National Medical Research Centre for Psychiatry and Neurology, 192019 Saint Petersburg, Russia
| | - German A. Shipulin
- Centre for Strategic Planning and Management of Biomedical Health Risks Management, 119121 Moscow, Russia
| | - Marina M. Petrova
- Shared Core Facilities “Molecular and Cell Technologies”, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
| | - Natalia P. Garganeeva
- Department of General Medical Practice and Outpatient Therapy, Siberian State Medical University, 634050 Tomsk, Russia
| | - Regina F. Nasyrova
- Institute of Personalized Psychiatry and Neurology, Shared Core Facilities, V.M. Bekhterev National Medical Research Centre for Psychiatry and Neurology, 192019 Saint Petersburg, Russia
- International Centre for Education and Research in Neuropsychiatry, Samara State Medical University, 443016 Samara, Russia
- Correspondence: (N.A.S.); (R.F.N.); Tel.: +7-(812)-620-02-20-78-13 (N.A.S. & R.F.N.)
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17
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A multimodal study of a first episode psychosis cohort: potential markers of antipsychotic treatment resistance. Mol Psychiatry 2022; 27:1184-1191. [PMID: 34642460 PMCID: PMC9001745 DOI: 10.1038/s41380-021-01331-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 09/17/2021] [Accepted: 09/29/2021] [Indexed: 11/13/2022]
Abstract
Treatment resistant (TR) psychosis is considered to be a significant cause of disability and functional impairment. Numerous efforts have been made to identify the clinical predictors of TR. However, the exploration of molecular and biological markers is still at an early stage. To understand the TR condition and identify potential molecular and biological markers, we analyzed demographic information, clinical data, structural brain imaging data, and molecular brain imaging data in 7 Tesla magnetic resonance spectroscopy from a first episode psychosis cohort that includes 136 patients. Age, gender, race, smoking status, duration of illness, and antipsychotic dosages were controlled in the analyses. We found that TR patients had a younger age at onset, more hospitalizations, more severe negative symptoms, a reduction in the volumes of the hippocampus (HP) and superior frontal gyrus (SFG), and a reduction in glutathione (GSH) levels in the anterior cingulate cortex (ACC), when compared to non-TR patients. The combination of multiple markers provided a better classification between TR and non-TR patients compared to any individual marker. Our study shows that ACC-GSH, HP and SFG volumes, and age at onset, could potentially be biomarkers for TR diagnosis, while hospitalization and negative symptoms could be used to evaluate the progression of the disease. Multimodal cohorts are essential in obtaining a comprehensive understanding of brain disorders.
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18
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Smucny J, Shi G, Davidson I. Deep Learning in Neuroimaging: Overcoming Challenges With Emerging Approaches. Front Psychiatry 2022; 13:912600. [PMID: 35722548 PMCID: PMC9200984 DOI: 10.3389/fpsyt.2022.912600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 05/06/2022] [Indexed: 12/12/2022] Open
Abstract
Deep learning (DL) is of great interest in psychiatry due its potential yet largely untapped ability to utilize multidimensional datasets (such as fMRI data) to predict clinical outcomes. Typical DL methods, however, have strong assumptions, such as large datasets and underlying model opaqueness, that are suitable for natural image prediction problems but not medical imaging. Here we describe three relatively novel DL approaches that may help accelerate its incorporation into mainstream psychiatry research and ultimately bring it into the clinic as a prognostic tool. We first introduce two methods that can reduce the amount of training data required to develop accurate models. These may prove invaluable for fMRI-based DL given the time and monetary expense required to acquire neuroimaging data. These methods are (1) transfer learning - the ability of deep learners to incorporate knowledge learned from one data source (e.g., fMRI data from one site) and apply it toward learning from a second data source (e.g., data from another site), and (2) data augmentation (via Mixup) - a self-supervised learning technique in which "virtual" instances are created. We then discuss explainable artificial intelligence (XAI), i.e., tools that reveal what features (and in what combinations) deep learners use to make decisions. XAI can be used to solve the "black box" criticism common in DL and reveal mechanisms that ultimately produce clinical outcomes. We expect these techniques to greatly enhance the applicability of DL in psychiatric research and help reveal novel mechanisms and potential pathways for therapeutic intervention in mental illness.
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Affiliation(s)
- Jason Smucny
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA, United States
| | - Ge Shi
- Department of Computer Sciences, University of California, Davis, Davis, CA, United States
| | - Ian Davidson
- Department of Computer Sciences, University of California, Davis, Davis, CA, United States
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19
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Xiao Y, Liao W, Long Z, Tao B, Zhao Q, Luo C, Tamminga CA, Keshavan MS, Pearlson GD, Clementz BA, Gershon ES, Ivleva EI, Keedy SK, Biswal BB, Mechelli A, Lencer R, Sweeney JA, Lui S, Gong Q. Subtyping Schizophrenia Patients Based on Patterns of Structural Brain Alterations. Schizophr Bull 2021; 48:241-250. [PMID: 34508358 PMCID: PMC8781382 DOI: 10.1093/schbul/sbab110] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Schizophrenia is a complex and heterogeneous syndrome. Whether quantitative imaging biomarkers can identify discrete subgroups of patients as might be used to foster personalized medicine approaches for patient care remains unclear. Cross-sectional structural MR images of 163 never-treated first-episode schizophrenia patients (FES) and 133 chronically ill patients with midcourse schizophrenia from the Bipolar and Schizophrenia Network for Intermediate Phenotypes (B-SNIP) consortium and a total of 403 healthy controls were recruited. Morphometric measures (cortical thickness, surface area, and subcortical structures) were extracted for each subject and then the optimized subtyping results were obtained with nonsupervised cluster analysis. Three subgroups of patients defined by distinct patterns of regional cortical and subcortical morphometric features were identified in FES. A similar three subgroup pattern was identified in the independent dataset of patients from the multi-site B-SNIP consortium. Similarities of classification patterns across these two patient cohorts suggest that the 3-group typology is relatively stable over the course of illness. Cognitive functions were worse in subgroup 1 with midcourse schizophrenia than those in subgroup 3. These findings provide novel insight into distinct subgroups of patients with schizophrenia based on structural brain features. Findings of different cognitive functions among the subgroups support clinical differences in the MRI-defined illness subtypes. Regardless of clinical presentation and stage of illness, anatomic MR subgrouping biomarkers can separate neurobiologically distinct subgroups of schizophrenia patients, which represent an important and meaningful step forward in differentiating subtypes of patients for studies of illness neurobiology and potentially for clinical trials.
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Affiliation(s)
- Yuan Xiao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Department of Psychiatry, University of Münster, Münster, Germany
| | - Wei Liao
- Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, Sichuan, China
| | - Zhiliang Long
- Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, Sichuan, China
| | - Bo Tao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiannan Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Chunyan Luo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, Yale University and Olin Neuropsychiatric Research Center, Hartford, CT, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Elliot S Gershon
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sarah K Keedy
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Rebekka Lencer
- Department of Psychiatry, University of Münster, Münster, Germany
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,To whom correspondence should be addressed; #37 GuoXue Xiang, Chengdu 610041, China; Tel: 86-28-85423960, Fax: 86-28-85423503; e-mail:
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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20
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Kokurcan A, Güriz SO, Karadağ H, Erdi F, Örsel S. Treatment strategies in management of schizophrenia patients with persistent symptoms in daily practice: a retrospective study. Int J Psychiatry Clin Pract 2021; 25:238-244. [PMID: 33555218 DOI: 10.1080/13651501.2021.1879157] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
OBJECTIVES One-third of the patients with schizophrenia show treatment resistance and literature on the effectiveness of interventions in patients with persistent symptoms is conflicting. This study aimed to assess clinical preferences of clinicians in those showing treatment resistance to antipsychotics and to determine correlates of interventions. METHODS Treatment strategies applied in the patients with schizophrenia in daily practice were inquired retrospectively. Those showing poor response to at least two antipsychotics and were administered a clinical intervention in a University Hospital between January and September 2018 were included. Clinical correlates of distinct interventions were evaluated. RESULTS The most common intervention (47%) was transition to a long-acting injectable antipsychotic (LAIA) and the second most common (22%) was addition of a second/third oral drug to on-going oral therapy. Switching to clozapine was more effective on positive symptoms comparing with the other interventions (p < 0.01). LAIA therapy showed a superiority over oral antipsychotic interventions at improving positive symptoms, except clozapine (p < 0.01). CONCLUSIONS LAIA administration and oral antipsychotic augmentation were the most common interventions in the patients with persistent symptoms. Clozapine was related to better clinical improvement in the present study and it might be administered as a second-line treatment in schizophrenia.Key pointsEffectiveness of the treatment strategies in schizophrenia patients with persistent symptoms is not satisfactory to meet expectations of the clinicians yet. Clozapine still seems to be the best option to provide a favourable improvement in TRS.LAIA and oral AP combination are used frequently in schizophrenia for persistent psychotic symptoms and targets of the combination therapies in daily practice needs to be clarified.The most common intervention was transition to a LAIA (47%) in the study and none of the patients administered LAIA had used a long-acting AP before the intervention. High rate of treatment nonadherence in schizophrenia is an important reason for common LAIA preference in the patients with persistent symptoms.Growing evidence indicates that clozapine can be used as a second-line treatment in schizophrenia, and thus, there is an urgent need to increase clozapine use in the patients with persistent symptoms in clinical practice.
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Affiliation(s)
- Ahmet Kokurcan
- Department of Psychiatry, Faculty of Medicine, Dışkapı Yıldırım Beyazıt Research and Training Hospital, Health Sciences University, Ankara, Turkey
| | - Seher Olga Güriz
- Department of Psychiatry, Faculty of Medicine, Dışkapı Yıldırım Beyazıt Research and Training Hospital, Health Sciences University, Ankara, Turkey
| | - Hasan Karadağ
- Department of Psychiatry, Faculty of Medicine, Dışkapı Yıldırım Beyazıt Research and Training Hospital, Health Sciences University, Ankara, Turkey
| | - Funda Erdi
- Department of Psychiatry, Faculty of Medicine, Dışkapı Yıldırım Beyazıt Research and Training Hospital, Health Sciences University, Ankara, Turkey
| | - Sibel Örsel
- Department of Psychiatry, Faculty of Medicine, Dışkapı Yıldırım Beyazıt Research and Training Hospital, Health Sciences University, Ankara, Turkey
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21
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D’Ambrosio E, Jauhar S, Kim S, Veronese M, Rogdaki M, Pepper F, Bonoldi I, Kotoula V, Kempton MJ, Turkheimer F, Kwon JS, Kim E, Howes OD. The relationship between grey matter volume and striatal dopamine function in psychosis: a multimodal 18F-DOPA PET and voxel-based morphometry study. Mol Psychiatry 2021; 26:1332-1345. [PMID: 31690805 PMCID: PMC7610423 DOI: 10.1038/s41380-019-0570-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 09/23/2019] [Accepted: 10/23/2019] [Indexed: 01/26/2023]
Abstract
A leading hypothesis for schizophrenia and related psychotic disorders proposes that cortical brain disruption leads to subcortical dopaminergic dysfunction, which underlies psychosis in the majority of patients who respond to treatment. Although supported by preclinical findings that prefrontal cortical lesions lead to striatal dopamine dysregulation, the relationship between prefrontal structural volume and striatal dopamine function has not been tested in people with psychosis. We therefore investigated the in vivo relationship between striatal dopamine synthesis capacity and prefrontal grey matter volume in treatment-responsive patients with psychosis, and compared them to treatment non-responsive patients, where dopaminergic mechanisms are not thought to be central. Forty patients with psychosis across two independent cohorts underwent 18F-DOPA PET scans to measure dopamine synthesis capacity (indexed as the influx rate constant Kicer) and structural 3T MRI. The PET, but not MR, data have been reported previously. Structural images were processed using DARTEL-VBM. GLM analyses were performed in SPM12 to test the relationship between prefrontal grey matter volume and striatal Kicer. Treatment responders showed a negative correlation between prefrontal grey matter and striatal dopamine synthesis capacity, but this was not evident in treatment non-responders. Specifically, we found an interaction between treatment response, whole striatal dopamine synthesis capacity and grey matter volume in left (pFWE corr. = 0.017) and right (pFWE corr. = 0.042) prefrontal cortex. We replicated the finding in right prefrontal cortex in the independent sample (pFWE corr. = 0.031). The summary effect size was 0.82. Our findings are consistent with the long-standing hypothesis of dysregulation of the striatal dopaminergic system being related to prefrontal cortex pathology in schizophrenia, but critically also extend the hypothesis to indicate it can be applied to treatment-responsive schizophrenia only. This suggests that different mechanisms underlie the pathophysiology of treatment-responsive and treatment-resistant schizophrenia.
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Affiliation(s)
- Enrico D’Ambrosio
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK,Psychiatric Neuroscience Group, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Sameer Jauhar
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK,Early Intervention Psychosis Clinical Academic Group, South London & Maudsley NHS Trust, London
| | - Seoyoung Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do, Republic of Korea
| | - Mattia Veronese
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Maria Rogdaki
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK,Psychiatric Imaging Group MRC London Institute of Medical Sciences, Hammersmith Hospital, London, W12 0NN, UK
| | - Fiona Pepper
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Ilaria Bonoldi
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Vasileia Kotoula
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Matthew J Kempton
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Federico Turkheimer
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Jun Soo Kwon
- Department of Brain & Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Euitae Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do, Republic of Korea. .,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Oliver D Howes
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK. .,Psychiatric Imaging Group MRC London Institute of Medical Sciences, Hammersmith Hospital, London, W12 0NN, UK.
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22
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Khosravi M. Ursodeoxycholic Acid in Patients With Treatment-Resistant Schizophrenia Suffering From Coronavirus Disease 2019: A Hypothesis Letter. Front Psychiatry 2021; 12:657316. [PMID: 33935842 PMCID: PMC8079749 DOI: 10.3389/fpsyt.2021.657316] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 03/01/2021] [Indexed: 12/20/2022] Open
Affiliation(s)
- Mohsen Khosravi
- Department of Psychiatry and Clinical Psychology, Zahedan University of Medical Sciences, Zahedan, Iran
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23
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Length of stay for inpatient incompetent to stand trial patients: importance of clinical and demographic variables. CNS Spectr 2020; 25:734-742. [PMID: 32286208 DOI: 10.1017/s1092852920001273] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE We investigated clinical and demographic variables to better understand their relationship to hospital length of stay for patients involuntarily committed to California state psychiatric hospitals under the state's incompetent to stand trial (IST) statutes. Additionally, we determined the most important variables in the model that influenced patient length of stay. METHODS We retrospectively studied all patients admitted as IST to California state psychiatric hospitals during the period January 1, 2010 through June 30, 2018 (N = 20 041). Primary diagnosis, total number of violent acts while hospitalized, age at admission, treating hospital, level of functioning at admission, ethnicity, sex, and having had a previous state hospital admission were evaluated using a parametric survival model. RESULTS The analysis showed that the most important variables related to length of stay were (1) diagnosis, (2) number of violent acts while hospitalized, and (3) age of admission. Specifically, longer length of stay was associated with (1) having a diagnosis of schizophrenia or neurocognitive disorder, (2) one or more violent acts, and (3) older age at admission. The other variables studied were also statistically significant, but not as influential in the model. CONCLUSIONS We found significant relations between length of stay and the variables studied, with the most important variables being (1) diagnosis, (2) number of physically violent acts, and (3) age at admission. These findings emphasize the need for treatments to target cognitive issues in the seriously mentally ill as well as treatment of violence and early identification of violence risk factors.
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24
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Zhuo C, Xu X, Lin X, Chen M, Ji F, Jiang D, Xu Y, Wang L, Li Y, Tian H, Wang W, Zhou C. Depressive symptoms combined with auditory hallucinations are accompanied with severe gray matter brain impairments in patients with first-episode untreated schizophrenia - A pilot study in China. Neurosci Lett 2020; 730:135033. [PMID: 32417389 DOI: 10.1016/j.neulet.2020.135033] [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: 12/26/2019] [Revised: 04/07/2020] [Accepted: 05/03/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Depressive symptoms and auditory hallucinations (AHs) are often accompanied by gray matter volume (GMV) alterations in schizophrenia. However, little is known about the effects of concurrent depressive symptoms and AHs on the GMV of patients with schizophrenia. AIM To investigate the pathological features of gray brain matter in patients with first-episode untreated schizophrenia (FUSCH) who have concurrent moderate-to-severe depressive symptoms and AHs (FUSCH-DAH). METHODS The Calgary Depression Scale for Schizophrenia (CDSS) and Auditory Hallucinations Rating Scale (AHRS) were adopted. Voxel-based morphometry (VBM)-based GMV analyses were used to measure cortical alterations. FUSCH-DAH patients were compared to FUSCH patients with depressive symptoms but without AHs, denoted as FUSCH-D, along with healthy controls. RESULTS GMV reductions were more substantial in the FUSCH-DAH patients than FUSCH-D patients or healthy controls. Both FUSCH-DAH and FUSCH-D groups showed GMV reductions of the parietal, frontal, and temporal lobes, which were not apparent in the healthy controls. Compared to FUSCH-D patients, FUSCH-DAH patients demonstrated more substantial GMV reductions in the Broca area, Wernicke region, insular lobe, and prefrontal lobe. The GMV reductions were 1.06% and 0.58% in FUSCH-DAH and FUSCH-D patients, respectively, as compared with the healthy controls. CONCLUSIONS This is the first report showing that concurrent depressive symptoms and AHs leads to severe GMV deterioration in FUSCH-DAH patients. Hence, there is a reciprocal relationship between AHs and depressive symptoms in FUSCH-DAH patients. However, the potential additive effects of concurrent AHs and depressive symptoms require further investigation in order to identify future targeted therapies for schizophrenia.
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Affiliation(s)
- Chuanjun Zhuo
- Department of Biological Psychiatry, School of Mental Health, Jining Medical University, Jining 272191, Shandong Province, China; Department of Psychiatry and Neuroimaging Center, Wenzhou Seventh People's Hospital, Wenzhou, 325000, Zhejiang Province, China; Psychiatric-Neuroimaging-Genetics and Comorbidity Laboratory (PNGC_Lab), Tianjin Anding Hospital, 300300 Tianjin, China.
| | - Xuexin Xu
- Department of Radiology, MRI Center, Tianjin Children Hospital, Tianjin Medical University Affiliated Tianjin Children Hospital, Tianjin 300444, China
| | - Xiaodong Lin
- Department of Psychiatry and Neuroimaging Center, Wenzhou Seventh People's Hospital, Wenzhou, 325000, Zhejiang Province, China
| | - Min Chen
- Department of Biological Psychiatry, School of Mental Health, Jining Medical University, Jining 272191, Shandong Province, China
| | - Feng Ji
- Department of Biological Psychiatry, School of Mental Health, Jining Medical University, Jining 272191, Shandong Province, China
| | - Deguo Jiang
- Department of Psychiatry and Neuroimaging Center, Wenzhou Seventh People's Hospital, Wenzhou, 325000, Zhejiang Province, China
| | - Yong Xu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China; MDT Center for Cognitive Impairment and Sleep Disorders, First Hospital of Shanxi Medical University, Taiyuan 030001, China
| | - Lina Wang
- Psychiatric-Neuroimaging-Genetics and Comorbidity Laboratory (PNGC_Lab), Tianjin Anding Hospital, 300300 Tianjin, China
| | - Yancheng Li
- Psychiatric-Neuroimaging-Genetics and Comorbidity Laboratory (PNGC_Lab), Tianjin Anding Hospital, 300300 Tianjin, China
| | - Hongjun Tian
- Psychiatric-Neuroimaging-Genetics and Comorbidity Laboratory (PNGC_Lab), Tianjin Anding Hospital, 300300 Tianjin, China
| | - Wenqiang Wang
- Canada and China Joint Laboratory of Biological Psychiatry, Xiamen Xianye Hospital, Xiamen 361000, Fujian Province, China
| | - Chunhua Zhou
- Department of Pharmacology, The First Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China
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25
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Treatment-resistant psychotic symptoms and the 15q11.2 BP1-BP2 (Burnside-Butler) deletion syndrome: case report and review of the literature. Transl Psychiatry 2020; 10:42. [PMID: 32066678 PMCID: PMC7026068 DOI: 10.1038/s41398-020-0725-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 12/17/2019] [Accepted: 01/08/2020] [Indexed: 12/25/2022] Open
Abstract
The 15q11.2 BP1-BP2 (Burnside-Butler) deletion is a rare copy number variant impacting four genes (NIPA1, NIPA2, CYFIP1, and TUBGCP5), and carries increased risks for developmental delay, intellectual disability, and neuropsychiatric disorders (attention-deficit/hyperactivity disorder, autism, and psychosis). In this case report (supported by extensive developmental information and medication history), we present the complex clinical portrait of a 44-year-old woman with 15q11.2 BP1-BP2 deletion syndrome and chronic, treatment-resistant psychotic symptoms who has resided nearly her entire adult life in a long-term state psychiatric institution. Diagnostic and treatment implications are discussed.
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26
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Crawford L, Loprinzi PD. Effects of Exercise on Memory Interference in Neuropsychiatric Disorders. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1228:425-438. [PMID: 32342475 DOI: 10.1007/978-981-15-1792-1_29] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Abstract
There are several mechanisms that cause memory impairment, including motivated forgetting, active forgetting, natural decay, and memory interference. Interference occurs when one is attempting to recall something specific, but there is conflicting information making it more difficult to recall the target stimuli. In laboratory settings, it is common to measure memory interference with paired associate tasks-usually utilizing the AB-CD, AB-AC, AB-ABr, or AB-DE AC-FG method. Memory impairments are frequent among those with neuropsychiatric disorders such as depression, schizophrenia, and multiple sclerosis. The memory effects of each condition differ, but are all related to alterations in brain physiology and general memory deterioration. Exercise, or physical activity, has been demonstrated to attenuate memory interference in some cases, but the mechanisms are still being determined. Further research is needed on memory interference, in regard to exercise and neuropsychiatric disorders.
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Affiliation(s)
- Lindsay Crawford
- Department of Health, Exercise Science, and Recreation Management, Exercise and Memory Laboratory, The University of Mississippi, MS, Oxford, USA
| | - Paul D Loprinzi
- Department of Health, Exercise Science, and Recreation Management, Exercise and Memory Laboratory, The University of Mississippi, MS, Oxford, USA.
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