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Hart XM, Gründer G, Ansermot N, Conca A, Corruble E, Crettol S, Cumming P, Hefner G, Frajerman A, Howes O, Jukic MM, Kim E, Kim S, Maniscalco I, Moriguchi S, Müller DJ, Nakajima S, Osugo M, Paulzen M, Ruhe HG, Scherf-Clavel M, Schoretsanitis G, Serretti A, Spina E, Spigset O, Steimer W, Süzen SH, Uchida H, Unterecker S, Vandenberghe F, Verstuyft C, Zernig G, Hiemke C, Eap CB. Optimisation of pharmacotherapy in psychiatry through therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests: Focus on antipsychotics. World J Biol Psychiatry 2024:1-86. [PMID: 38913780 DOI: 10.1080/15622975.2024.2366235] [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: 11/04/2023] [Revised: 05/12/2024] [Accepted: 06/06/2024] [Indexed: 06/26/2024]
Abstract
BACKGROUND For psychotic disorders (i.e. schizophrenia), pharmacotherapy plays a key role in controlling acute and long-term symptoms. To find the optimal individual dose and dosage strategy, specialised tools are used. Three tools have been proven useful to personalise drug treatments: therapeutic drug monitoring (TDM) of drug levels, pharmacogenetic testing (PG), and molecular neuroimaging. METHODS In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 45 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)). RESULTS Study results strongly support the use of TDM and the cytochrome P450 (CYP) genotyping and/or phenotyping to guide drug therapies. Evidence-based target ranges are available for titrating drug doses that are often supported by PET findings. CONCLUSION All three tools discussed in these Guidelines are essential for drug treatment. TDM goes well beyond typical indications such as unclear compliance and polypharmacy. Despite its enormous potential to optimise treatment effects, minimise side effects and ultimately reduce the global burden of diseases, personalised drug treatment has not yet become the standard of care in psychiatry.
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Affiliation(s)
- Xenia Marlene Hart
- Department of Molecular Neuroimaging, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Gerhard Gründer
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
- German Center for Mental Health (DZPG), Partner Site Mannheim, Heidelberg, Germany
| | - Nicolas Ansermot
- Department of Psychiatry, Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Lausanne University Hospital, Prilly, Switzerland
| | - Andreas Conca
- Dipartimento di Psichiatria, Comprensorio Sanitario di Bolzano, Bolzano, Italy
| | - Emmanuelle Corruble
- Service Hospitalo-Universitaire de Psychiatrie, Hôpital de Bicêtre, Université Paris-Saclay, AP-HP, Le Kremlin-Bicêtre, France
- Equipe MOODS, Inserm U1018, CESP (Centre de Recherche en Epidémiologie et Sante des Populations), Le Kremlin-Bicêtre, France
| | - Severine Crettol
- Department of Psychiatry, Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Lausanne University Hospital, Prilly, Switzerland
| | - Paul Cumming
- Department of Nuclear Medicine, Bern University Hospital, Bern, Switzerland
- School of Psychology and Counseling, Queensland University of Technology, Brisbane, Australia
| | - Gudrun Hefner
- Forensic Psychiatry, Vitos Clinic for Forensic Psychiatry, Eltville, Germany
| | - Ariel Frajerman
- Service Hospitalo-Universitaire de Psychiatrie, Hôpital de Bicêtre, Université Paris-Saclay, AP-HP, Le Kremlin-Bicêtre, France
- Equipe MOODS, Inserm U1018, CESP (Centre de Recherche en Epidémiologie et Sante des Populations), Le Kremlin-Bicêtre, France
| | - Oliver Howes
- Department of Psychosis Studies, IoPPN, King's College London, London, UK
- Faculty of Medicine, Institute of Clinical Sciences (ICS), Imperial College London, London, UK
| | - Marin M Jukic
- Department of Physiology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
- Pharmacogenetics Section, Department of Physiology and Pharmacology, Karolinska Institutet, Solna, Sweden
| | - Euitae Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Seoyoung Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Republic of Korea
| | - Ignazio Maniscalco
- Dipartimento di Psichiatria, Comprensorio Sanitario di Bolzano, Bolzano, Italy
| | - Sho Moriguchi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Daniel J Müller
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, Germany
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Martin Osugo
- Department of Psychosis Studies, IoPPN, King's College London, London, UK
- Faculty of Medicine, Institute of Clinical Sciences (ICS), Imperial College London, London, UK
| | - Michael Paulzen
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- JARA - Translational Brain Medicine, Alexianer Center for Mental Health, Aachen, Germany
| | - Henricus Gerardus Ruhe
- Department of Psychiatry, Radboudumc, Nijmegen, Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, Netherlands
| | - Maike Scherf-Clavel
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, Germany
| | - Georgios Schoretsanitis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | | | - Edoardo Spina
- Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy
| | - Olav Spigset
- Department of Clinical Pharmacology, St. Olav University Hospital, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Werner Steimer
- Institute of Clinical Chemistry and Pathobiochemistry, Technical University Munich, Munich, Germany
| | - Sinan H Süzen
- Department of Pharmaceutic Toxicology, Faculty of Pharmacy, Ankara University, Ankara, Turkey
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Stefan Unterecker
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, Germany
| | - Frederik Vandenberghe
- Department of Psychiatry, Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Lausanne University Hospital, Prilly, Switzerland
| | - Celine Verstuyft
- Equipe MOODS, Inserm U1018, CESP (Centre de Recherche en Epidémiologie et Sante des Populations), Le Kremlin-Bicêtre, France
- Department of Molecular Genetics, Pharmacogenetics and Hormonology, Bicêtre University Hospital Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Gerald Zernig
- Department of Pharmacology, Medical University Innsbruck, Hall in Tirol, Austria
- Private Practice for Psychotherapy and Court-Certified Witness, Hall in Tirol, Austria
| | - Christoph Hiemke
- Department of Psychiatry and Psychotherapy and Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center of Mainz, Mainz, Germany
| | - Chin B Eap
- Department of Psychiatry, Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Lausanne University Hospital, Prilly, Switzerland
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland
- Center for Research and Innovation in Clinical Pharmaceutical Sciences, University of Lausanne, Lausanne, Switzerland
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, University of Lausanne, Lausanne, Switzerland
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2
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Sharew NT, Clark SR, Schubert KO, Amare AT. Pharmacogenomic scores in psychiatry: systematic review of current evidence. Transl Psychiatry 2024; 14:322. [PMID: 39107294 PMCID: PMC11303815 DOI: 10.1038/s41398-024-02998-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 06/21/2024] [Accepted: 06/27/2024] [Indexed: 08/10/2024] Open
Abstract
In the past two decades, significant progress has been made in the development of polygenic scores (PGSs). One specific application of PGSs is the development and potential use of pharmacogenomic- scores (PGx-scores) to identify patients who can benefit from a specific medication or are likely to experience side effects. This systematic review comprehensively evaluates published PGx-score studies in psychiatry and provides insights into their potential clinical use and avenues for future development. A systematic literature search was conducted across PubMed, EMBASE, and Web of Science databases until 22 August 2023. This review included fifty-three primary studies, of which the majority (69.8%) were conducted using samples of European ancestry. We found that over 90% of PGx-scores in psychiatry have been developed based on psychiatric and medical diagnoses or trait variants, rather than pharmacogenomic variants. Among these PGx-scores, the polygenic score for schizophrenia (PGSSCZ) has been most extensively studied in relation to its impact on treatment outcomes (32 publications). Twenty (62.5%) of these studies suggest that individuals with higher PGSSCZ have negative outcomes from psychotropic treatment - poorer treatment response, higher rates of treatment resistance, more antipsychotic-induced side effects, or more psychiatric hospitalizations, while the remaining studies did not find significant associations. Although PGx-scores alone accounted for at best 5.6% of the variance in treatment outcomes (in schizophrenia treatment resistance), together with clinical variables they explained up to 13.7% (in bipolar lithium response), suggesting that clinical translation might be achieved by including PGx-scores in multivariable models. In conclusion, our literature review found that there are still very few studies developing PGx-scores using pharmacogenomic variants. Research with larger and diverse populations is required to develop clinically relevant PGx-scores, using biology-informed and multi-phenotypic polygenic scoring approaches, as well as by integrating clinical variables with these scores to facilitate their translation to psychiatric practice.
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Affiliation(s)
- Nigussie T Sharew
- Discipline of Psychiatry, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia
- Asrat Woldeyes Health Science Campus, Debre Berhan University, Debre Berhan, Ethiopia
| | - Scott R Clark
- Discipline of Psychiatry, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia
| | - K Oliver Schubert
- Discipline of Psychiatry, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia
- Division of Mental Health, Northern Adelaide Local Health Network, SA Health, Adelaide, Australia
- Headspace Adelaide Early Psychosis - Sonder, Adelaide, SA, Australia
| | - Azmeraw T Amare
- Discipline of Psychiatry, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia.
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Farooq S, Hattle M, Kingstone T, Ajnakina O, Dazzan P, Demjaha A, Murray RM, Di Forti M, Jones PB, Doody GA, Shiers D, Andrews G, Milner A, Nettis MA, Lawrence AJ, van der Windt DA, Riley RD. Development and initial evaluation of a clinical prediction model for risk of treatment resistance in first-episode psychosis: Schizophrenia Prediction of Resistance to Treatment (SPIRIT). Br J Psychiatry 2024:1-10. [PMID: 39101211 DOI: 10.1192/bjp.2024.101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/06/2024]
Abstract
BACKGROUND A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication. AIMS To develop and evaluate a model that could predict the risk of TRS in routine clinical practice. METHOD We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model. RESULTS We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model's C-statistic was 0.727 (95% CI 0.723-0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism. CONCLUSIONS We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.
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Affiliation(s)
- Saeed Farooq
- School of Medicine, Keele University, Newcastle-under-Lyme, UK; National Institute for Health and Care Research (NIHR), UK; and St George's Hospital, Midlands Partnership University NHS Foundation Trust, Stafford, UK
| | - Miriam Hattle
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; and National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK
| | - Tom Kingstone
- School of Medicine, Keele University, Newcastle-under-Lyme, UK; National Institute for Health and Care Research (NIHR), UK; and St George's Hospital, Midlands Partnership University NHS Foundation Trust, Stafford, UK
| | - Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; and Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Arsime Demjaha
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; and Department of Psychiatry, Experimental Biomedicine and Clinical Neuroscience, University of Palermo, Palermo, Italy
| | - Marta Di Forti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Gillian A Doody
- Division of Psychiatry and Applied Psychology, University of Nottingham, Nottingham, UK
| | - David Shiers
- School of Medicine, Keele University, Newcastle-under-Lyme, UK; Psychosis Research Unit, Greater Manchester Mental Health NHS Trust, Manchester, UK; and University of Manchester, Manchester, UK
| | - Gabrielle Andrews
- St George's Hospital, Midlands Partnership University NHS Foundation Trust, Stafford, UK
| | - Abbie Milner
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; and National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK
| | - Maria Antonietta Nettis
- South London and Maudsley NHS Foundation Trust, London, UK; and Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Andrew J Lawrence
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Danielle A van der Windt
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; and National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK
| | - Richard D Riley
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; and National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK
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4
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Singh S, Stocco G, Theken KN, Dickson A, Feng Q, Karnes JH, Mosley JD, El Rouby N. Pharmacogenomics polygenic risk score: Ready or not for prime time? Clin Transl Sci 2024; 17:e13893. [PMID: 39078255 PMCID: PMC11287822 DOI: 10.1111/cts.13893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2024] [Revised: 06/11/2024] [Accepted: 06/25/2024] [Indexed: 07/31/2024] Open
Abstract
Pharmacogenomic Polygenic Risk Scores (PRS) have emerged as a tool to address the polygenic nature of pharmacogenetic phenotypes, increasing the potential to predict drug response. Most pharmacogenomic PRS have been extrapolated from disease-associated variants identified by genome wide association studies (GWAS), although some have begun to utilize genetic variants from pharmacogenomic GWAS. As pharmacogenomic PRS hold the promise of enabling precision medicine, including stratified treatment approaches, it is important to assess the opportunities and challenges presented by the current data. This assessment will help determine how pharmacogenomic PRS can be advanced and transitioned into clinical use. In this review, we present a summary of recent evidence, evaluate the current status, and identify several challenges that have impeded the progress of pharmacogenomic PRS. These challenges include the reliance on extrapolations from disease genetics and limitations inherent to pharmacogenomics research such as low sample sizes, phenotyping inconsistencies, among others. We finally propose recommendations to overcome the challenges and facilitate the clinical implementation. These recommendations include standardizing methodologies for phenotyping, enhancing collaborative efforts, developing new statistical methods to capitalize on drug-specific genetic associations for PRS construction. Additional recommendations include enhancing the infrastructure that can integrate genomic data with clinical predictors, along with implementing user-friendly clinical decision tools, and patient education. Ethical and regulatory considerations should address issues related to patient privacy, informed consent and safe use of PRS. Despite these challenges, ongoing research and large-scale collaboration is likely to advance the field and realize the potential of pharmacogenomic PRS.
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Affiliation(s)
- Sonal Singh
- Merck & Co., IncSouth San FranciscoCaliforniaUSA
| | - Gabriele Stocco
- Department of Medical, Surgical and Health SciencesUniversity of TriesteTriesteItaly
- Institute for Maternal and Child Health IRCCS Burlo GarofoloTriesteItaly
| | - Katherine N. Theken
- Department of Oral and Maxillofacial Surgery and Pharmacology, School of Dental MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Alyson Dickson
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - QiPing Feng
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Jason H. Karnes
- Department of Pharmacy Practice and Science, R. Ken Coit College of PharmacyUniversity of ArizonaTucsonArizonaUSA
- Department of Biomedical InformaticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Jonathan D. Mosley
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Biomedical InformaticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Nihal El Rouby
- Division of Pharmacy Practice and Adminstrative Sciences, James L Winkle College of PharmacyUniversity of CincinnatiCincinnatiOhioUSA
- St. Elizabeth HealthcareEdgewoodKentuckyUSA
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Segura AG, Serna EDL, Sugranyes G, Baeza I, Valli I, Martínez-Serrano I, Díaz-Caneja CM, Andreu-Bernabeu Á, Moreno DM, Gassó P, Rodríguez N, Martínez-Pinteño A, Prohens L, Torrent C, García-Rizo C, Mas S, Castro-Fornieles J. Polygenic risk scores mediating functioning outcomes through cognitive and clinical features in youth at family risk and controls. Eur Neuropsychopharmacol 2024; 81:28-37. [PMID: 38310718 DOI: 10.1016/j.euroneuro.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 02/06/2024]
Abstract
Schizophrenia and bipolar disorder exhibit substantial clinical overlap, particularly in individuals at familial high risk, who frequently present sub-threshold symptoms before the onset of illness. Severe mental disorders are highly polygenic traits, but their impact on the stages preceding the manifestation of mental disorders remains relatively unexplored. Our study aimed to examine the influence of polygenic risk scores (PRS) on sub-clinical outcomes over a 2-year period in youth at familial high risk for schizophrenia and bipolar disorder and controls. The sample included 222 children and adolescents, comprising offspring of parents with schizophrenia (n = 38), bipolar disorder (n = 80), and community controls (n = 104). We calculated PRS for psychiatric disorders, neuroticism and cognition using the PRS-CS method. Linear mixed-effects models were employed to investigate the association between PRS and cognition, symptom severity and functioning. Mediation analyses were conducted to explore whether clinical features acted as intermediaries in the impact of PRS on functioning outcomes. SZoff exhibited elevated PRS for schizophrenia. In the entire sample, PRS for depression, neuroticism, and cognitive traits showed associations with sub-clinical features. The effect of PRS for neuroticism and general intelligence on functioning outcomes were mediated by cognition and symptoms severity, respectively. This study delves into the interplay among genetics, the emergence of sub-clinical symptoms and functioning outcomes, providing novel evidence on mechanisms underpinning the continuum from sub-threshold features to the onset of mental disorders. The findings underscore the interplay of genetics, cognition, and clinical features, providing insights for personalized early interventions.
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Affiliation(s)
- Alex G Segura
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Elena de la Serna
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Gisela Sugranyes
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Inmaculada Baeza
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Isabel Valli
- Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Irene Martínez-Serrano
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Álvaro Andreu-Bernabeu
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Dolores M Moreno
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Adolescent Inpatient Unit, Department of Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Psychiatry Department, Universidad Complutense de Madrid, Madrid, Spain
| | - Patricia Gassó
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Natalia Rodríguez
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Albert Martínez-Pinteño
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Llucia Prohens
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Carla Torrent
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Barcelona Bipolar Disorders Program, Clinical Institute of Neuroscience, Hospital Clinic, University of Barcelona, Fundació Clinic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Clemente García-Rizo
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Barcelona Clinic Schizophrenia Unit, Institute of Neuroscience, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Sergi Mas
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
| | - Josefina Castro-Fornieles
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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De Pieri M, Ferrari M, Pistis G, Gamma F, Marino F, Von Gunten A, Conus P, Cosentino M, Eap CB. Prediction of antipsychotics efficacy based on a polygenic risk score: a real-world cohort study. Front Pharmacol 2024; 15:1274442. [PMID: 38523642 PMCID: PMC10958197 DOI: 10.3389/fphar.2024.1274442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 01/26/2024] [Indexed: 03/26/2024] Open
Abstract
Background: Response to antipsychotics is subject to a wide interindividual variability, due to genetic and non-genetic factors. Several single nucleotide polymorphisms (SNPs) have been associated with response to antipsychotics in genome-wide association studies (GWAS). Polygenic risk scores (PRS) are a powerful tool to aggregate into a single measure the small effects of multiple risk alleles. Materials and methods: We studied the association between a PRS composed of SNPs associated with response to antipsychotics in GWAS studies (PRSresponse) in a real-world sample of patients (N = 460) with different diagnoses (schizophrenia spectrum, bipolar, depressive, neurocognitive, substance use disorders and miscellaneous). Two other PRSs composed of SNPs previously associated with risk of schizophrenia (PRSschizophrenia1 and PRSschizophrenia2) were also tested for their association with response to treatment. Results: PRSresponse was significantly associated with response to antipsychotics considering the whole cohort (OR = 1.14, CI = 1.03-1.26, p = 0.010), the subgroup of patients with schizophrenia, schizoaffective disorder or bipolar disorder (OR = 1.18, CI = 1.02-1.37, p = 0.022, N = 235), with schizophrenia or schizoaffective disorder (OR = 1.24, CI = 1.04-1.47, p = 0.01, N = 176) and with schizophrenia (OR = 1.27, CI = 1.04-1.55, p = 0.01, N = 149). Sensitivity and specificity were sub-optimal (schizophrenia 62%, 61%; schizophrenia spectrum 56%, 55%; schizophrenia spectrum plus bipolar disorder 60%, 56%; all patients 63%, 58%, respectively). PRSschizophrenia1 and PRSschizophrenia2 were not significantly associated with response to treatment. Conclusion: PRSresponse defined from GWAS studies is significantly associated with response to antipsychotics in a real-world cohort; however, the results of the sensitivity-specificity analysis preclude its use as a predictive tool in clinical practice.
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Affiliation(s)
- Marco De Pieri
- Center for Research in Medical Pharmacology, Varese, Italy
- PhD Program in Clinical and Experimental Medicine and Medical Humanities, University of Insubria, Varese, Italy
- General Psychiatry Service, Hopitaux Universitaires de Genève, Geneva, Switzerland
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Marco Ferrari
- Center for Research in Medical Pharmacology, Varese, Italy
| | - Giorgio Pistis
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Franziska Gamma
- Les Toises Psychiatry and Psychotherapy Center, Lausanne, Switzerland
| | - Franca Marino
- Center for Research in Medical Pharmacology, Varese, Italy
| | - Armin Von Gunten
- Service of Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Philippe Conus
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | | | - Chin-Bin Eap
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland
- Center for Research and Innovation in Clinical Pharmaceutical Sciences, University of Lausanne, Lausanne, Switzerland
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, University of Lausanne, Lausanne, Switzerland
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7
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Kendler KS, Ohlsson H, Sundquist J, Sundquist K. The relationship between familial-genetic risk and pharmacological treatment in a Swedish national sample of patients with major depression, bipolar disorder, and schizophrenia. Mol Psychiatry 2024; 29:742-749. [PMID: 38123723 DOI: 10.1038/s41380-023-02365-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 11/28/2023] [Accepted: 12/01/2023] [Indexed: 12/23/2023]
Abstract
Using Swedish registers, we examine whether the prescription of and the response to antidepressants (AD), mood stabilizers (MS), and antipsychotics (AP) in the treatment of, respectively, major depression (MD), bipolar disorder (BD), and schizophrenia (SZ), are influenced by familial-genetic risk. We examined individuals born in Sweden 1960-1995 with a first diagnosis of MD (n = 257,177), BD (n = 23,032), and SZ (n = 4248) from 2006 to 2018. Drug classes and Defined Daily Dose (DDD) were obtained from the Pharmacy register using the Anatomical Therapeutic Chemical system. We utilized the Familial Genetic Risk Scores (FGRS) calculated from morbidity risks in first- through fifth degree relatives. Treatment with antidepressants (AD) in MD, mood-stabilizers (MS) in BD, and antipsychotics (AP) in SZ were associated with significantly higher disorder-specific familial-genetic risks. Using dosage trajectory analysis of AD, MS, and AP treatment for MD, BD, and SZ, respectively, familial-genetic risk was positively associated with higher and/or increasing drug dosages over time. For MD and BD, examining cases started on the most common pharmacologic treatment class (SSRIs for MD and "other anti-epileptics" for BD), familial-genetic risks were significantly lower in those who did not versus did later receive treatment from other AD and MS classes, respectively. Higher familial-genetic risk for BD predicted switching AD medication in cases of MD. Among pharmacologically treated cases of BD, familial-genetic risk was significantly higher for those treated with lithium. In a large population-based patient cohort, we found evidence of a wide-spread association between higher familial-genetic risk and i) increased likelihood of receiving pharmacologic treatment but 2) responding more poorly to it-as indicated by a switching of medications -- and/or requiring higher doses. Further investigations into the clinical utility of genetic risk scores in the clinical managements of MD, BD, and SZ are warranted.
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Affiliation(s)
- Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA.
| | - Henrik Ohlsson
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Jan Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
- Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kristina Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
- Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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8
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Kogure M, Kanahara N, Miyazawa A, Shiko Y, Otsuka I, Matsuyama K, Takase M, Kimura M, Kimura H, Ota K, Idemoto K, Tamura M, Oda Y, Yoshida T, Okazaki S, Yamasaki F, Nakata Y, Watanabe Y, Niitsu T, Hishimoto A, Iyo M. Association of SLC6A3 variants with treatment-resistant schizophrenia: a genetic association study of dopamine-related genes in schizophrenia. Front Psychiatry 2024; 14:1334335. [PMID: 38476817 PMCID: PMC10929739 DOI: 10.3389/fpsyt.2023.1334335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 12/21/2023] [Indexed: 03/14/2024] Open
Abstract
Background Most genetic analyses that have attempted to identify a locus or loci that can distinguish patients with treatment-resistant schizophrenia (TRS) from those who respond to treatment (non-TRS) have failed. However, evidence from multiple studies suggests that patients with schizophrenia who respond well to antipsychotic medication have a higher dopamine (DA) state in brain synaptic clefts whereas patients with TRS do not show enhanced DA synthesis/release pathways. Patients and methods To examine the contribution (if any) of genetics to TRS, we conducted a genetic association analysis of DA-related genes in schizophrenia patients (TRS, n = 435; non-TRS, n = 539) and healthy controls (HC: n = 489). Results The distributions of the genotypes of rs3756450 and the 40-bp variable number tandem repeat on SLC6A3 differed between the TRS and non-TRS groups. Regarding rs3756450, the TRS group showed a significantly higher ratio of the A allele, whereas the non-TRS group predominantly had the G allele. The analysis of the combination of COMT and SLC6A3 yielded a significantly higher ratio of the putative low-DA type (i.e., high COMT activity + high SLC6A3 activity) in the TRS group compared to the two other groups. Patients with the low-DA type accounted for the minority of the non-TRS group and exhibited milder psychopathology. Conclusion The overall results suggest that (i) SLC6A3 could be involved in responsiveness to antipsychotic medication and (ii) genetic variants modulating brain DA levels may be related to the classification of TRS and non-TRS.
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Affiliation(s)
- Masanobu Kogure
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Nobuhisa Kanahara
- Division of Medical Treatment and Rehabilitation, Center for Forensic Mental Health, Chiba University, Chiba, Japan
| | - Atsuhiro Miyazawa
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
- Doujin-kai Kisarazu Hospital, Kisarazu, Japan
| | - Yuki Shiko
- Biostatistics Section, Clinical Research Center, Chiba University Hospital, Chiba, Japan
| | - Ikuo Otsuka
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Koichi Matsuyama
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
- Douwa-kai Chiba Hospital, Funabashi, Japan
| | | | - Makoto Kimura
- Chiba Psychiatric Medical Center, Chiba, Japan
- Department of Psychiatry, Kameda Medical Center, Kamogawa, Japan
| | - Hiroshi Kimura
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
- Gakuji-kai Kimura Hospital, Chiba, Japan
- Department of Psychiatry, School of Medicine, International University of Health and Welfare, Narita, Japan
| | - Kiyomitsu Ota
- Doujin-kai Kisarazu Hospital, Kisarazu, Japan
- Choshi-kokoro Clinic, Choshi, Japan
| | - Keita Idemoto
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
- Doujin-kai Kisarazu Hospital, Kisarazu, Japan
| | - Masaki Tamura
- Doujin-kai Kisarazu Hospital, Kisarazu, Japan
- Department of Cognitive Behavioral Psychology, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Yasunori Oda
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
| | | | - Satoshi Okazaki
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Fumiaki Yamasaki
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Yusuke Nakata
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
| | | | - Tomihisa Niitsu
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Akitoyo Hishimoto
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Masaomi Iyo
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
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9
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Lim K, Yee JY, See YM, Ng BT, Zheng S, Tang C, Lencz T, Lee J, Lam M. Deconstructing the genetic architecture of treatment-resistant schizophrenia in East Asian ancestry. Asian J Psychiatr 2023; 90:103826. [PMID: 37944474 DOI: 10.1016/j.ajp.2023.103826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 10/29/2023] [Accepted: 10/31/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Treatment-resistant schizophrenia (TRS) affects a substantial proportion of patients who do not respond adequately to antipsychotic medications, yet the underlying biological mechanism remains poorly understood. This study investigates the link between the genetic predisposition to schizophrenia and TRS. METHODS 857 individuals diagnosed with schizophrenia were divided into TRS (n = 142) and non-TRS (n = 715) based on well-defined TRS criteria. Polygenic risk scores (PRS) were calculated using schizophrenia genome-wide association summary statistics from East-Asian and European ancestry populations. PRS was estimated using both P-value thresholding and Bayesian framework methods. Logistic regression analyses were performed to differentiate between TRS and non-TRS individuals. RESULTS The schizophrenia PRS derived from the East-Asian training dataset effectively distinguished between TRS and non-TRS individuals (R2 = 0.029, p = 4.86 ×10-5, pT = 0.1, OR = 1.52, 95% CI = 1.242-1.861), with higher PRS values observed in the TRS group. Similar PRS analysis was conducted based on the European ancestry GWAS summary statistics, but we found superior prediction based on the East-Asian ancestry discovery data. CONCLUSION This study reveals an association between common risk variants for schizophrenia and TRS status, suggesting that the genetic burden of schizophrenia may partly contribute to treatment resistance in individuals with schizophrenia. These findings propose the potential use of genetic risk factors for early TRS identification and timely access to clozapine. However, the ancestral background of the discovery sample is crucial for successfully implementing PRS in clinical settings.
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Affiliation(s)
- Keane Lim
- Research Division, Institute of Mental Health, Singapore
| | - Jie Yin Yee
- Research Division, Institute of Mental Health, Singapore
| | - Yuen Mei See
- Research Division, Institute of Mental Health, Singapore
| | - Boon Tat Ng
- Department of Pharmacy, Institute of Mental Health, Singapore
| | - Shushan Zheng
- Department of Psychosis, Institute of Mental Health, Singapore
| | - Charmaine Tang
- Department of Psychosis, Institute of Mental Health, Singapore
| | - Todd Lencz
- Feinstein Institutes for Medical Research, NY, USA
| | - Jimmy Lee
- Department of Psychosis, Institute of Mental Health, Singapore; Population and Global Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
| | - Max Lam
- Research Division, Institute of Mental Health, Singapore; Feinstein Institutes for Medical Research, NY, USA; Population and Global Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
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10
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Zhai S, Mehrotra DV, Shen J. Applying polygenic risk score methods to pharmacogenomics GWAS: challenges and opportunities. Brief Bioinform 2023; 25:bbad470. [PMID: 38152980 PMCID: PMC10782924 DOI: 10.1093/bib/bbad470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 11/20/2023] [Accepted: 11/28/2023] [Indexed: 12/29/2023] Open
Abstract
Polygenic risk scores (PRSs) have emerged as promising tools for the prediction of human diseases and complex traits in disease genome-wide association studies (GWAS). Applying PRSs to pharmacogenomics (PGx) studies has begun to show great potential for improving patient stratification and drug response prediction. However, there are unique challenges that arise when applying PRSs to PGx GWAS beyond those typically encountered in disease GWAS (e.g. Eurocentric or trans-ethnic bias). These challenges include: (i) the lack of knowledge about whether PGx or disease GWAS/variants should be used in the base cohort (BC); (ii) the small sample sizes in PGx GWAS with corresponding low power and (iii) the more complex PRS statistical modeling required for handling both prognostic and predictive effects simultaneously. To gain insights in this landscape about the general trends, challenges and possible solutions, we first conduct a systematic review of both PRS applications and PRS method development in PGx GWAS. To further address the challenges, we propose (i) a novel PRS application strategy by leveraging both PGx and disease GWAS summary statistics in the BC for PRS construction and (ii) a new Bayesian method (PRS-PGx-Bayesx) to reduce Eurocentric or cross-population PRS prediction bias. Extensive simulations are conducted to demonstrate their advantages over existing PRS methods applied in PGx GWAS. Our systematic review and methodology research work not only highlights current gaps and key considerations while applying PRS methods to PGx GWAS, but also provides possible solutions for better PGx PRS applications and future research.
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Affiliation(s)
- Song Zhai
- Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ 07065, USA
| | - Devan V Mehrotra
- Biostatistics and Research Decision Sciences, Merck & Co., Inc., North Wales, PA 19454, USA
| | - Judong Shen
- Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ 07065, USA
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11
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Owen MJ, Legge SE, Rees E, Walters JTR, O'Donovan MC. Genomic findings in schizophrenia and their implications. Mol Psychiatry 2023; 28:3638-3647. [PMID: 37853064 PMCID: PMC10730422 DOI: 10.1038/s41380-023-02293-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 10/02/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023]
Abstract
There has been substantial progress in understanding the genetics of schizophrenia over the past 15 years. This has revealed a highly polygenic condition with the majority of the currently explained heritability coming from common alleles of small effect but with additional contributions from rare copy number and coding variants. Many specific genes and loci have been implicated that provide a firm basis upon which mechanistic research can proceed. These point to disturbances in neuronal, and particularly synaptic, functions that are not confined to a small number of brain regions and circuits. Genetic findings have also revealed the nature of schizophrenia's close relationship to other conditions, particularly bipolar disorder and childhood neurodevelopmental disorders, and provided an explanation for how common risk alleles persist in the population in the face of reduced fecundity. Current genomic approaches only potentially explain around 40% of heritability, but only a small proportion of this is attributable to robustly identified loci. The extreme polygenicity poses challenges for understanding biological mechanisms. The high degree of pleiotropy points to the need for more transdiagnostic research and the shortcomings of current diagnostic criteria as means of delineating biologically distinct strata. It also poses challenges for inferring causality in observational and experimental studies in both humans and model systems. Finally, the Eurocentric bias of genomic studies needs to be rectified to maximise benefits and ensure these are felt across diverse communities. Further advances are likely to come through the application of new and emerging technologies, such as whole-genome and long-read sequencing, to large and diverse samples. Substantive progress in biological understanding will require parallel advances in functional genomics and proteomics applied to the brain across developmental stages. For these efforts to succeed in identifying disease mechanisms and defining novel strata they will need to be combined with sufficiently granular phenotypic data.
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Affiliation(s)
- Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
| | - Sophie E Legge
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Elliott Rees
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
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12
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Farrell M, Dietterich TE, Harner MK, Bruno LM, Filmyer DM, Shaughnessy RA, Lichtenstein ML, Britt AM, Biondi TF, Crowley JJ, Lázaro-Muñoz G, Forsingdal AE, Nielsen J, Didriksen M, Berg JS, Wen J, Szatkiewicz J, Mary Xavier R, Sullivan PF, Josiassen RC. Increased Prevalence of Rare Copy Number Variants in Treatment-Resistant Psychosis. Schizophr Bull 2023; 49:881-892. [PMID: 36454006 PMCID: PMC10318882 DOI: 10.1093/schbul/sbac175] [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] [Indexed: 12/03/2022]
Abstract
BACKGROUND It remains unknown why ~30% of patients with psychotic disorders fail to respond to treatment. Previous genomic investigations of treatment-resistant psychosis have been inconclusive, but some evidence suggests a possible link between rare disease-associated copy number variants (CNVs) and worse clinical outcomes in schizophrenia. Here, we identified schizophrenia-associated CNVs in patients with treatment-resistant psychotic symptoms and then compared the prevalence of these CNVs to previously published schizophrenia cases not selected for treatment resistance. METHODS CNVs were identified using chromosomal microarray (CMA) and whole exome sequencing (WES) in 509 patients with treatment-resistant psychosis (a lack of clinical response to ≥3 adequate antipsychotic medication trials over at least 5 years of psychiatric hospitalization). Prevalence of schizophrenia-associated CNVs in this sample was compared to that in a previously published large schizophrenia cohort study. RESULTS Integrating CMA and WES data, we identified 47 cases (9.2%) with at least one CNV of known or possible neuropsychiatric risk. 4.7% (n = 24) carried a known neurodevelopmental risk CNV. The prevalence of well-replicated schizophrenia-associated CNVs was 4.1%, with duplications of the 16p11.2 and 15q11.2-q13.1 regions, and deletions of the 22q11.2 chromosomal region as the most frequent CNVs. Pairwise loci-based analysis identified duplications of 15q11.2-q13.1 to be independently associated with treatment resistance. CONCLUSIONS These findings suggest that CNVs may uniquely impact clinical phenotypes beyond increasing risk for schizophrenia and may potentially serve as biological entry points for studying treatment resistance. Further investigation will be necessary to elucidate the spectrum of phenotypic characteristics observed in adult psychiatric patients with disease-associated CNVs.
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Affiliation(s)
- Martilias Farrell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | | | - Lisa M Bruno
- Translational Neuroscience, LLC, Conshohocken, PA, USA
| | | | | | | | - Allison M Britt
- School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tamara F Biondi
- Office of the Vice Chancellor for Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - James J Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Gabriel Lázaro-Muñoz
- Center for Bioethics, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | | | - Jacob Nielsen
- Division of Neuroscience, H. Lundbeck A/S, Valby, Denmark
| | | | - Jonathan S Berg
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jin Szatkiewicz
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rose Mary Xavier
- School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Patrick F Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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13
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Segura AG, Mezquida G, Martínez-Pinteño A, Gassó P, Rodriguez N, Moreno-Izco L, Amoretti S, Bioque M, Lobo A, González-Pinto A, García-Alcon A, Roldán-Bejarano A, Vieta E, de la Serna E, Toll A, Cuesta MJ, Mas S, Bernardo M. Link between cognitive polygenic risk scores and clinical progression after a first-psychotic episode. Psychol Med 2023; 53:4634-4647. [PMID: 35678455 PMCID: PMC10388335 DOI: 10.1017/s0033291722001544] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 05/05/2022] [Accepted: 05/09/2022] [Indexed: 11/05/2022]
Abstract
BACKGROUND Clinical intervention in early stages of psychotic disorders is crucial for the prevention of severe symptomatology trajectories and poor outcomes. Genetic variability is studied as a promising modulator of prognosis, thus novel approaches considering the polygenic nature of these complex phenotypes are required to unravel the mechanisms underlying the early progression of the disorder. METHODS The sample comprised of 233 first-episode psychosis (FEP) subjects with clinical and cognitive data assessed periodically for a 2-year period and 150 matched controls. Polygenic risk scores (PRSs) for schizophrenia, bipolar disorder, depression, education attainment and cognitive performance were used to assess the genetic risk of FEP and to characterize their association with premorbid, baseline and progression of clinical and cognitive status. RESULTS Schizophrenia, bipolar disorder and cognitive performance PRSs were associated with an increased risk of FEP [false discovery rate (FDR) ⩽ 0.027]. In FEP patients, increased cognitive PRSs were found for FEP patients with more cognitive reserve (FDR ⩽ 0.037). PRSs reflecting a genetic liability for improved cognition were associated with a better course of symptoms, functionality and working memory (FDR ⩽ 0.039). Moreover, the PRS of depression was associated with a worse trajectory of the executive function and the general cognitive status (FDR ⩽ 0.001). CONCLUSIONS Our study provides novel evidence of the polygenic bases of psychosis and its clinical manifestation in its first stage. The consistent effect of cognitive PRSs on the early clinical progression suggests that the mechanisms underlying the psychotic episode and its severity could be partially independent.
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Affiliation(s)
- Alex G. Segura
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Gisela Mezquida
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
- Barcelona Clínic Schizophrenia Unit, Neuroscience Institute Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
| | - Albert Martínez-Pinteño
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Patricia Gassó
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
| | - Natalia Rodriguez
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Lucía Moreno-Izco
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Silvia Amoretti
- Barcelona Clínic Schizophrenia Unit, Neuroscience Institute Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Group of Psychiatry, Mental Health and Addictions, Psychiatric Genetics Unit, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Miquel Bioque
- Barcelona Clínic Schizophrenia Unit, Neuroscience Institute Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Antonio Lobo
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain
- Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain
| | - Ana González-Pinto
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Hospital Universitario de Alava, Vitoria-Gasteiz, Spain
- Instituto de Investigación Sanitaria Bioaraba, Vitoria-Gasteiz, Spain
- University of the Basque Country, Vizcaya, Spain
| | - Alicia García-Alcon
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
| | - Alexandra Roldán-Bejarano
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Psychiatry Department, Institut d'Investigació Biomèdica-SantPau (IIB-SANTPAU), Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Eduard Vieta
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, Barcelona, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Elena de la Serna
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
- Department of Child and Adolescent Psychiatry and Psychology, Clínic Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Alba Toll
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institute of Neuropsychiatry and Addiction, Parc de Salut Mar, Barcelona, Spain
- Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Manuel J. Cuesta
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Sergi Mas
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
| | - Miquel Bernardo
- Barcelona Clínic Schizophrenia Unit, Neuroscience Institute Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPs), Barcelona, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
| | - PEPs Group
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
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Sagud M, Tudor L, Nedic Erjavec G, Nikolac Perkovic M, Uzun S, Mimica N, Madzarac Z, Zivkovic M, Kozumplik O, Konjevod M, Svob Strac D, Pivac N. Genotypic and Haplotypic Association of Catechol- O-Methyltransferase rs4680 and rs4818 Gene Polymorphisms with Particular Clinical Symptoms in Schizophrenia. Genes (Basel) 2023; 14:1358. [PMID: 37510262 PMCID: PMC10379812 DOI: 10.3390/genes14071358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 06/22/2023] [Accepted: 06/26/2023] [Indexed: 07/30/2023] Open
Abstract
Catechol-O-methyl transferase (COMT) gene variants are involved in different neuropsychiatric disorders and cognitive impairments, associated with altered dopamine function. This study investigated the genotypic and haplotypic association of COMT rs4680 and rs4618 polymorphisms with the severity of cognitive and other clinical symptoms in 544 male and 385 female subjects with schizophrenia. COMT rs4818 G carriers were more frequent in male patients with mild abstract thinking difficulties, compared to CC homozygotes or C allele carriers. Male carriers of COMT rs4680 A allele had worse abstract thinking (N5) scores than GG carriers, whereas AA homozygotes were more frequent in male subjects with lower scores on the intensity of the somatic concern (G1) item, compared to G carriers. Male carriers of COMT rs4818-rs4680 GA haplotype had the highest scores on the G1 item (somatic concern), whereas GG haplotype carriers had the lowest scores on G2 (anxiety) and G6 (depression) items. COMT GG haplotype was less frequent in female patients with severe disturbance of volition (G13 item) compared to the group with mild symptoms, while CG haplotype was more frequent in female patients with severe then mild symptoms. These findings suggest the sex-specific genotypic and haplotypic association of COMT variants with a severity of cognitive and other clinical symptoms of schizophrenia.
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Affiliation(s)
- Marina Sagud
- Department for Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, 10000 Zagreb, Croatia; (M.S.); (Z.M.); (M.Z.)
- School of Medicine, University of Zagreb, 10000 Zagreb, Croatia; (S.U.); (N.M.)
| | - Lucija Tudor
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Ruder Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.); (D.S.S.)
| | - Gordana Nedic Erjavec
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Ruder Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.); (D.S.S.)
| | - Matea Nikolac Perkovic
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Ruder Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.); (D.S.S.)
| | - Suzana Uzun
- School of Medicine, University of Zagreb, 10000 Zagreb, Croatia; (S.U.); (N.M.)
- Department for Biological Psychiatry and Psychogeriatrics, University Psychiatric Hospital Vrapce, 10090 Zagreb, Croatia;
| | - Ninoslav Mimica
- School of Medicine, University of Zagreb, 10000 Zagreb, Croatia; (S.U.); (N.M.)
- Department for Biological Psychiatry and Psychogeriatrics, University Psychiatric Hospital Vrapce, 10090 Zagreb, Croatia;
| | - Zoran Madzarac
- Department for Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, 10000 Zagreb, Croatia; (M.S.); (Z.M.); (M.Z.)
| | - Maja Zivkovic
- Department for Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, 10000 Zagreb, Croatia; (M.S.); (Z.M.); (M.Z.)
| | - Oliver Kozumplik
- Department for Biological Psychiatry and Psychogeriatrics, University Psychiatric Hospital Vrapce, 10090 Zagreb, Croatia;
| | - Marcela Konjevod
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Ruder Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.); (D.S.S.)
| | - Dubravka Svob Strac
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Ruder Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.); (D.S.S.)
| | - Nela Pivac
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Ruder Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.); (D.S.S.)
- University of Applied Sciences Hrvatsko Zagorje Krapina, 49000 Krapina, Croatia
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15
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Psychotic disorders as a framework for precision psychiatry. Nat Rev Neurol 2023; 19:221-234. [PMID: 36879033 DOI: 10.1038/s41582-023-00779-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/24/2023] [Indexed: 03/08/2023]
Abstract
People with psychotic disorders can show marked interindividual variations in the onset of illness, responses to treatment and relapse, but they receive broadly similar clinical care. Precision psychiatry is an approach that aims to stratify people with a given disorder according to different clinical outcomes and tailor treatment to their individual needs. At present, interindividual differences in outcomes of psychotic disorders are difficult to predict on the basis of clinical assessment alone. Therefore, current research in psychosis seeks to build models that predict outcomes by integrating clinical information with a range of biological measures. Here, we review recent progress in the application of precision psychiatry to psychotic disorders and consider the challenges associated with implementing this approach in clinical practice.
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16
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Facal F, Costas J. Polygenic risk scores for schizophrenia and treatment resistance: New data, systematic review and meta-analysis. Schizophr Res 2023; 252:189-197. [PMID: 36657363 DOI: 10.1016/j.schres.2023.01.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/14/2022] [Accepted: 01/05/2023] [Indexed: 01/18/2023]
Affiliation(s)
- Fernando Facal
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain; Servizo de Psiquiatría, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain; Universidade de Santiago de Compostela (USC), Galicia, Spain
| | - Javier Costas
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain.
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17
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Lin BD, Pinzón-Espinosa J, Blouzard E, van der Horst MZ, Okhuijsen-Pfeifer C, van Eijk KR, Guloksuz S, Peyrot WJ, Luykx JJ. Associations Between Polygenic Risk Score Loading, Psychosis Liability, and Clozapine Use Among Individuals With Schizophrenia. JAMA Psychiatry 2023; 80:181-185. [PMID: 36542388 PMCID: PMC9857760 DOI: 10.1001/jamapsychiatry.2022.4234] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/18/2022] [Indexed: 12/24/2022]
Abstract
Importance Predictors consistently associated with psychosis liability and course of illness in schizophrenia (SCZ) spectrum disorders (SSD), including the need for clozapine treatment, are lacking. Longitudinally ascertained medication use may empower studies examining associations between polygenic risk scores (PRSs) and pharmacotherapy choices. Objective To examine associations between PRS-SCZ loading and groups with different liabilities to SSD (individuals with SSD taking clozapine, individuals with SSD taking other antipsychotics, their parents and siblings, and unrelated healthy controls) and between PRS-SCZ and the likelihood of receiving a prescription of clozapine relative to other antipsychotics. Design, Setting, and Participants This genetic association study was a multicenter, observational cohort study with 6 years of follow-up. Included were individuals diagnosed with SSD who were taking clozapine or other antipsychotics, their parents and siblings, and unrelated healthy controls. Data were collected from 2004 until 2021 and analyzed between October 2021 and September 2022. Exposures Polygenic risk scores for SCZ. Main Outcomes and Measures Multinomial logistic regression was used to examine possible differences between groups by computing risk ratios (RRs), ie, ratios of the probability of pertaining to a particular group divided by the probability of healthy control status. We also computed PRS-informed odd ratios (ORs) for clozapine use relative to other antipsychotics. Results Polygenic risk scores for SCZ were generated for 2344 participants (mean [SD] age, 36.95 years [14.38]; 994 female individuals [42.4%]) who remained after quality control screening (557 individuals with SSD taking clozapine, 350 individuals with SSD taking other antipsychotics during the 6-year follow-up, 542 parents and 574 siblings of individuals with SSD, and 321 unrelated healthy controls). All RRs were significantly different from 1; RRs were highest for individuals with SSD taking clozapine (RR, 3.24; 95% CI, 2.76-3.81; P = 2.47 × 10-46), followed by individuals with SSD taking other antipsychotics (RR, 2.30; 95% CI, 1.95-2.72; P = 3.77 × 10-22), parents (RR, 1.44; 95% CI, 1.25-1.68; P = 1.76 × 10-6), and siblings (RR, 1.40; 95% CI, 1.21-1.63; P = 8.22 × 10-6). Polygenic risk scores for SCZ were positively associated with clozapine vs other antipsychotic use (OR, 1.41; 95% CI, 1.22-1.63; P = 2.98 × 10-6), suggesting a higher likelihood of clozapine prescriptions among individuals with higher PRS-SCZ. Conclusions and Relevance In this study, PRS-SCZ loading differed between groups of individuals with SSD, their relatives, and unrelated healthy controls, with patients taking clozapine at the far end of PRS-SCZ loading. Additionally, PRS-SCZ was associated with a higher likelihood of clozapine prescribing. Our findings may inform early intervention and prognostic studies of the value of using PRS-SCZ to personalize antipsychotic treatment.
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Affiliation(s)
- Bochao D. Lin
- Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, Maastricht, the Netherlands
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, School of Basic Medical Sciences, Henan University, Kaifeng, China
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
| | - Justo Pinzón-Espinosa
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
- Sant Pau Mental Health Group, Institut d’Investigació Biomèdica Sant Pau (IBB-Sant Pau), Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB), Barcelona, Catalonia, Spain
- Department of Medicine, School of Medicine, University of Barcelona, Barcelona, Spain
- Department of Clinical Psychiatry, School of Medicine, University of Panama, Panama City, Panama
| | - Elodie Blouzard
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
| | - Marte Z. van der Horst
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
- GGNet Mental Health, Warnsveld, the Netherlands
| | - Cynthia Okhuijsen-Pfeifer
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
| | - Kristel R. van Eijk
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Wouter J. Peyrot
- Department of Psychiatry, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
| | - Jurjen J. Luykx
- Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, Maastricht, the Netherlands
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
- GGNet Mental Health, Warnsveld, the Netherlands
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18
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Osimo EF, Perry BI, Mallikarjun P, Pritchard M, Lewis J, Katunda A, Murray GK, Perez J, Jones PB, Cardinal RN, Howes OD, Upthegrove R, Khandaker GM. Predicting treatment resistance from first-episode psychosis using routinely collected clinical information. NATURE MENTAL HEALTH 2023; 1:25-35. [PMID: 37034013 PMCID: PMC7614410 DOI: 10.1038/s44220-022-00001-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 11/03/2022] [Indexed: 01/21/2023]
Abstract
Around a quarter of people who experience a first episode of psychosis (FEP) will develop treatment-resistant schizophrenia (TRS), but there are currently no established clinically useful methods to predict this from baseline. We aimed to explore the predictive potential for clozapine use as a proxy for TRS of routinely collected, objective biomedical predictors at FEP onset, and to externally validate the model in a separate clinical sample of people with FEP. We developed and externally validated a forced-entry logistic regression risk prediction Model fOr cloZApine tReaTment, or MOZART, to predict up to 8-year risk of clozapine use from FEP using routinely recorded information including age, sex, ethnicity, triglycerides, alkaline phosphatase levels, and lymphocyte counts. We also produced a least-absolute shrinkage and selection operator (LASSO) based model, additionally including neutrophil count, smoking status, body mass index, and random glucose levels. The models were developed using data from two UK psychosis early intervention services (EIS) and externally validated in another UK EIS. Model performance was assessed via discrimination and calibration. We developed the models in 785 patients, and validated externally in 1,110 patients. Both models predicted clozapine use well at internal validation (MOZART: C 0.70; 95%CI 0.63,0.76; LASSO: 0.69; 95%CI 0.63,0.77). At external validation, discrimination performance reduced (MOZART: 0.63; 0.58,0.69; LASSO: 0.64; 0.58,0.69) but recovered after re-estimation of the lymphocyte predictor (C: 0.67; 0.62,0.73). Calibration plots showed good agreement between observed and predicted risk in the forced-entry model. We also present a decision-curve analysis and an online data visualisation tool. The use of routinely collected clinical information including blood-based biomarkers taken at FEP onset can help to predict the individual risk of clozapine use, and should be considered equally alongside other potentially useful information such as symptom scores in large-scale efforts to predict psychiatric outcomes.
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Affiliation(s)
- Emanuele F. Osimo
- Imperial College London Institute of Clinical Sciences and UKRI MRC London Institute of Medical Sciences, Hammersmith Hospital Campus, London, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Benjamin I. Perry
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Pavan Mallikarjun
- Institute for Mental Health and Centre for Human Brain Health, University of Birmingham, Birmingham, England
- Birmingham Early Intervention Service, Birmingham Women’s and Children’s NHS Foundation trust
| | | | - Jonathan Lewis
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Asia Katunda
- Birmingham Early Intervention Service, Birmingham Women’s and Children’s NHS Foundation trust
| | - Graham K. Murray
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Jesus Perez
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- Norwich Medical School, University of East Anglia. Norwich, UK
- Applied Research Collaboration East of England, National Institute for Health Research (NIHR), UK
- Institute of Biomedical Research of Salamanca (IBSAL); Psychiatry Unit, Department of Medicine, University of Salamanca, Salamanca, Spain
| | - Peter B. Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- Applied Research Collaboration East of England, National Institute for Health Research (NIHR), UK
| | - Rudolf N. Cardinal
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Oliver D. Howes
- Imperial College London Institute of Clinical Sciences and UKRI MRC London Institute of Medical Sciences, Hammersmith Hospital Campus, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, De Crespigny Park, London, SE5 8AF, UK
| | - Rachel Upthegrove
- Institute for Mental Health and Centre for Human Brain Health, University of Birmingham, Birmingham, England
- Birmingham Early Intervention Service, Birmingham Women’s and Children’s NHS Foundation trust
| | - Golam M. Khandaker
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, England
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, England
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19
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Vasiliu O. The pharmacogenetics of the new-generation antipsychotics - A scoping review focused on patients with severe psychiatric disorders. Front Psychiatry 2023; 14:1124796. [PMID: 36873203 PMCID: PMC9978195 DOI: 10.3389/fpsyt.2023.1124796] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 01/30/2023] [Indexed: 02/18/2023] Open
Abstract
Exploring the possible correlations between gene variations and the clinical effects of the new-generation antipsychotics is considered essential in the framework of personalized medicine. It is expected that pharmacogenetic data will be useful for increasing the treatment efficacy, tolerability, therapeutic adherence, functional recovery, and quality of life in patients with severe psychiatric disorders (SPD). This scoping review investigated the available evidence about the pharmacokinetics, pharmacodynamics, and pharmacogenetics of five new-generation antipsychotics, i.e., cariprazine, brexpiprazole, aripiprazole, lumateperone, and pimavanserin. Based on the analysis of 25 primary and secondary sources and the review of these agents' summaries of product characteristics, aripiprazole benefits from the most relevant data about the impact of gene variability on its pharmacokinetics and pharmacodynamics, with significant consequences on this antipsychotic's efficacy and tolerability. The determination of the CYP2D6 metabolizer status is important when administering aripiprazole, either as monotherapy or associated with other pharmacological agents. Allelic variability in genes encoding dopamine D2, D3, and serotonin, 5HT2A, 5HT2C receptors, COMT, BDNF, and dopamine transporter DAT1 was also associated with different adverse events or variations in the clinical efficacy of aripiprazole. Brexpiprazole also benefits from specific recommendations regarding the CYP2D6 metabolizer status and the risks of associating this antipsychotic with strong/moderate CYP2D6 or CYP3A4 inhibitors. US Food and Drug Administration (FDA) and European Medicines Agency (EMA) recommendations about cariprazine refer to possible pharmacokinetic interactions with strong CYP3A4 inhibitors or inducers. Pharmacogenetic data about cariprazine is sparse, and relevant information regarding gene-drug interactions for lumateperone and pimavanserin is yet lacking. In conclusion, more studies are needed to detect the influence of gene variations on the pharmacokinetics and pharmacodynamics of new-generation antipsychotics. This type of research could increase the ability of clinicians to predict favorable responses to specific antipsychotics and to improve the tolerability of the treatment regimen in patients with SPD.
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Affiliation(s)
- Octavian Vasiliu
- Department of Psychiatry, Dr. Carol Davila Central Military Emergency University Hospital, Bucharest, Romania
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20
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Keat K, Hui D, Xiao B, Bradford Y, Cindi Z, Daar ES, Gulick R, Riddler SA, Sinxadi P, Haas DW, Ritchie MD. Leveraging Multi-Ancestry Polygenic Risk Scores for Body Mass Index to Predict Antiretroviral Therapy-Induced Weight Gain. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2023; 28:233-244. [PMID: 36540980 PMCID: PMC10091400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Widespread availability of antiretroviral therapies (ART) for HIV-1 have generated considerable interest in understanding the pharmacogenomics of ART. In some individuals, ART has been associated with excessive weight gain, which disproportionately affects women of African ancestry. The underlying biology of ART-associated weight gain is poorly understood, but some genetic markers which modify weight gain risk have been suggested, with more genetic factors likely remaining undiscovered. To overcome limitations in available sample sizes for genome-wide association studies (GWAS) in people with HIV, we explored whether a multi-ancestry polygenic risk score (PRS) derived from large, publicly available non-HIV GWAS for body mass index (BMI) can achieve high cross-ancestry performance for predicting baseline BMI in diverse, prospective ART clinical trials datasets, and whether that PRSBMI is also associated with change in BMI over 48 weeks on ART. We show that PRSBMI explained ∼5-7% of variability in baseline (pre-ART) BMI, with high performance in both European and African genetic ancestry groups, but that PRSBMI was not associated with change in BMI on ART. This study argues against a shared genetic predisposition for baseline (pre-ART) BMI and ART-associated weight gain.
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Affiliation(s)
- Karl Keat
- Genomics and Computational Biology Graduate Program
| | - Daniel Hui
- Genomics and Computational Biology Graduate Program
| | - Brenda Xiao
- Genomics and Computational Biology Graduate Program
| | - Yuki Bradford
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zinhle Cindi
- Division of Clinical Pharmacology, Department of Medicine University of Cape Town, Cape Town, South Africa
| | - Eric S. Daar
- Lundquist Institute at Harbor-UCLA Medical Center Torrance, CA 90502, USA
| | - Roy Gulick
- Weill Cornell Medicine, New York, New York, NY 10065, USA
| | | | - Phumla Sinxadi
- Division of Clinical Pharmacology, Department of Medicine University of Cape Town, Cape Town, South Africa
| | - David W. Haas
- Vanderbilt University Medical Center, Nashville, TN, USA
- Meharry Medical College, Nashville, TN, USA
| | - Marylyn D. Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Biomedical Informatics University of Pennsylvania, Philadelphia, PA 19104, USA
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21
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Fusar-Poli L, Rutten BPF, van Os J, Aguglia E, Guloksuz S. Polygenic risk scores for predicting outcomes and treatment response in psychiatry: hope or hype? Int Rev Psychiatry 2022; 34:663-675. [PMID: 36786114 DOI: 10.1080/09540261.2022.2101352] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Abstract
Over the last years, the decreased costs and enhanced accessibility to large genome-wide association studies datasets have laid the foundations for the development of polygenic risk scores (PRSs). A PRS is calculated on the weighted sum of single nucleotide polymorphisms and measures the individual genetic predisposition to develop a certain phenotype. An increasing number of studies have attempted to utilize the PRSs for risk stratification and prognostic evaluation. The present narrative review aims to discuss the potential clinical utility of PRSs in predicting outcomes and treatment response in psychiatry. After summarizing the evidence on major mental disorders, we have discussed the advantages and limitations of currently available PRSs. Although PRSs represent stable trait features with a normal distribution in the general population and can be relatively easily calculated in terms of time and costs, their real-world applicability is reduced by several limitations, such as low predictive power and lack of population diversity. Even with the rapid expansion of the psychiatric genetic knowledge base, pure genetic prediction in clinical psychiatry appears to be out of reach in the near future. Therefore, combining genomic and exposomic vulnerabilities for mental disorders with a detailed clinical characterization is needed to personalize care.
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Affiliation(s)
- Laura Fusar-Poli
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Catania, Italy
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands.,UMC Utrecht Brain Centre, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands.,Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Eugenio Aguglia
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Catania, Italy
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
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22
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Facal F, Arrojo M, Paz E, Páramo M, Costas J. Association between psychiatric hospitalizations of patients with schizophrenia and polygenic risk scores based on genes with altered expression by antipsychotics. Acta Psychiatr Scand 2022; 146:139-150. [PMID: 35582973 DOI: 10.1111/acps.13444] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 05/13/2022] [Accepted: 05/15/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To test whether a schizophrenia polygenic risk score (PRS) based on the subset of polymorphisms that affect brain expression of genes with altered expression by antipsychotics (exprAP PRS) is associated with psychiatric readmission of patients with schizophrenia. METHODS The study involved 427 patients with schizophrenia. Genes with altered expression by antipsychotics were extracted from the Comparative Toxigenomics Database. ExprAP PRS was estimated using the clumping and thresholding (p < 0.05) method. Two additional PRS were tested based on subsets of exprAP polymorphisms whose schizophrenia risk allele has the same (unrestored PRS) or opposite (restored PRS) direction of effect on gene expression than antipsychotics. A general SCZ PRS was tested for comparison. Logistic and ordinal regression were used to test for association of each PRS with ever readmission and admission history, an outcome based on length and number of admissions, respectively. Webgestalt was used for Gene Ontology enrichment analysis. RESULTS ExprAP PRS was associated with ever readmission (OR = 1.48, 95%CI:1.10-1.97) and admission history (OR = 1.30, 95%CI 1.07-1.57). SCZ PRS (OR = 1.22, 95%CI: 1.01-1.48) and unrestored PRS (OR = 1.26, 95%CI 1.04-1.53) were only associated with admission history. Genes at exprAP PRS were enriched in regulation of cytokine production. CONCLUSION Our findings suggest that PRS based on genes with altered expression by antipsychotics may be better predictors of readmission than SCZ PRS, warranting further investigation in larger cohorts of patients. The action of antipsychotics may be related to brain gene expression, mainly in genes involved in immunity.
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Affiliation(s)
- Fernando Facal
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain.,Servizo de Psiquiatría, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain.,Universidade de Santiago de Compostela (USC), Santiago de Compostela, Galicia, Spain
| | - Manuel Arrojo
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain.,Servizo de Psiquiatría, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain
| | - Eduardo Paz
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain.,Servizo de Psiquiatría, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain
| | - Mario Páramo
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain.,Servizo de Psiquiatría, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain
| | - Javier Costas
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain
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23
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Zhang Y, Du X, Fu Y, Zhao Q, Wang Z, Qin W, Zhang Q. Effects of polygenic risk score of type 2 diabetes on the hippocampal topological property and episodic memory. Brain Imaging Behav 2022; 16:2506-2516. [PMID: 35904672 DOI: 10.1007/s11682-022-00706-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/10/2022] [Indexed: 11/02/2022]
Abstract
Type 2 diabetes is associated with a higher risk of dementia. The pathogenesis is complex and partly influenced by genetic factors. The hippocampus is the most vulnerable brain region in individuals with type 2 diabetes. However, whether the genetic risk of type 2 diabetes is associated with the hippocampus and episodic memory remains unclear. This study explored the influence of polygenic risk score (PRS) of type 2 diabetes on the white matter topological properties of the hippocampus among individuals with and without type 2 diabetes and its associations with episodic memory. This study included 103 individuals with type 2 diabetes and 114 well-matched individuals without type 2 diabetes. All the participants were genotyped, and a diffusion tensor imaging-based structural network was constructed. PRS was calculated based on a genome-wide association study of type 2 diabetes. The PRS-by-disease interactions on the bilateral hippocampal topological network properties were evaluated by analysis of covariance (ANCOVA). There were significant PRS-by-disease interaction effects on the nodal topological properties of the right hippocampus node. In the individuals with type 2 diabetes, the PRS was correlated with the right hippocampal nodal properties, and the nodal properties were correlated with the episodic memory. In addition, the right hippocampal nodal properties mediated the effect of PRS on episodic memory in individuals with type 2 diabetes. Our results suggested a gene-brain-cognition biological pathway, which might help understand the neural mechanism of the genetic risk of type 2 diabetes affects episodic memory in type 2 diabetes.
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Affiliation(s)
- Yang Zhang
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Xin Du
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Yumeng Fu
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Qiuyue Zhao
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Zirui Wang
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Wen Qin
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Quan Zhang
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China. .,Department of Medical Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, 300052, Tianjin, China.
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24
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Werner MCF, Wirgenes KV, Shadrin AA, Lunding SH, Rødevand L, Hjell G, Ormerod MBEG, Haram M, Agartz I, Djurovic S, Melle I, Aukrust P, Ueland T, Andreassen OA, Steen NE. Limited association between infections, autoimmune disease and genetic risk and immune activation in severe mental disorders. Prog Neuropsychopharmacol Biol Psychiatry 2022; 116:110511. [PMID: 35063598 DOI: 10.1016/j.pnpbp.2022.110511] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 12/23/2021] [Accepted: 01/13/2022] [Indexed: 10/19/2022]
Abstract
BACKGROUND Low-grade inflammation may be part of the underlying mechanism of schizophrenia and bipolar disorder. We investigated if genetic susceptibility, infections or autoimmunity could explain the immune activation. METHODS Seven immune markers were selected based on indicated associations to severe mental disorders (IL-1Ra, sIL-2R, IL-18, sgp130, sTNFR-1, APRIL, ICAM-1) and measured in plasma of patients with schizophrenia (SCZ, N = 732) and bipolar spectrum disorders (BD, N = 460) and healthy controls (HC, N = 938). Information on rate of infections and autoimmune diseases were obtained from Norwegian national health registries for a twelve-year period. Polygenic risk scores (PRS) of SCZ and BD were calculated from genome-wide association studies. Analysis of covariance were used to test effects of infection rate, autoimmune disease and PRS on differences in immune markers between patients and HC. RESULTS Infection rate differed between all groups (BD > HC > SCZ, all p < 0.001) whereas autoimmune disease was more frequent in BD compared to SCZ (p = 0.004) and HC (p = 0.003). sIL-2R was positively associated with autoimmune disease (p = 0.001) and negatively associated with PRS of SCZ (p = 0.006) across SCZ and HC; however, associations represented only small changes in the difference of sIL-2R levels between SCZ and HC. CONCLUSION There were few significant associations between rate of infections, autoimmune disease or PRS and altered immune markers in SCZ and BD, and the detected associations represented only small changes in the immune aberrations. The findings suggest that most of the low-grade inflammation in SCZ and BD is explained by other factors than the underlying PRS, autoimmunity and infection rates.
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Affiliation(s)
- Maren Caroline Frogner Werner
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Katrine Verena Wirgenes
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Alexey A Shadrin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Synve Hoffart Lunding
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Linn Rødevand
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gabriela Hjell
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry, Ostfold Hospital, Graalum, Norway
| | | | - Marit Haram
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ingrid Melle
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pål Aukrust
- Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway; Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Thor Ueland
- Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway; K.G. Jebsen - Thrombosis Research and Expertise Center (TREC), University of Tromsø, Tromsø, Norway
| | - Ole Andreas Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nils Eiel Steen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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25
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Zazueta A, Castillo T, Cavieres Á, González R, Abarca M, Nieto RR, Deneken J, Araneda C, Moya PR, Bustamante ML. Polymorphisms in Schizophrenia-Related Genes Are Potential Predictors of Antipsychotic Treatment Resistance and Refractoriness. Int J Neuropsychopharmacol 2022; 25:701-708. [PMID: 35416253 PMCID: PMC9515128 DOI: 10.1093/ijnp/pyac025] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 03/11/2022] [Accepted: 03/30/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Approximately 30% of individuals with schizophrenia (SZ) are resistant to conventional antipsychotic drug therapy (AP). Of these, one-third are also resistant to the second-line treatment, clozapine. Treatment resistance and refractoriness are associated with increased morbidity and disability, making timely detection of these issues critical. Variability in treatment responsiveness is partly genetic, but research has yet to identify variants suitable for personalizing antipsychotic prescriptions. METHODS We evaluated potential associations between response to AP and candidate gene variants previously linked to SZ or treatment response. Two groups of patients with SZ were evaluated: one receiving clozapine (n = 135) and the other receiving another second-generation AP (n = 61). Single-nucleotide polymorphisms (SNPs) in the genes OXT, OXTR, CNR1, DDC, and DRD2 were analyzed. RESULTS Several SNPs were associated with response vs. resistance to AP or clozapine. CONCLUSIONS This is the first study of its kind, to our knowledge, in our admixed Chilean population to address the complete treatment response spectrum. We identified SNPs predictive of treatment-resistant SZ in the genes OXT, CNR1, DDC, and DRD2.
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Affiliation(s)
| | | | - Álvaro Cavieres
- Psychiatry Department, School of Medicine, Universidad de Valparaíso, Valparaíso, Chile
| | - René González
- Instituto de Fisiología, Facultad de Ciencias, Universidad de Valparaíso, Valparaíso, Chile
| | - Maximiliano Abarca
- Psychiatry Department, School of Medicine, Universidad de Valparaíso, Valparaíso, Chile
| | - Rodrigo R Nieto
- University Psychiatric Clinic, Clinical Hospital, Universidad de Chile, Santiago, Chile,Department of Psychiatry and Mental Health (North Division), Faculty of Medicine, Universidad de Chile, Santiago, Chile,Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Javier Deneken
- University Psychiatric Clinic, Clinical Hospital, Universidad de Chile, Santiago, Chile,Human Genetics Program, Biomedical Sciences Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Cristian Araneda
- Laboratorio de Genética y Biotecnología en Acuicultura, Departamento de Producción Animal, Facultad de Ciencias Agronómicas, Universidad de Chile, Santiago, Chile
| | - Pablo R Moya
- Correspondence: Pablo R. Moya, PhD, Instituto de Fisiologia, Facultad de Ciencias, Universidad de Valparaiso, Av. Gran Bretana 1111, Valparaiso, Chile ()
| | - M Leonor Bustamante
- Correspondence: M. Leonor Bustamante, MD, PhD, Human Genetics Program, Biomedical Sciences Institute, Facultad de Medicina, Universidad de Chile, Independencia 1027, Independencia, Sabtiago, Chile ()
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26
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Farooq S, Hattle M, Dazzan P, Kingstone T, Ajnakina O, Shiers D, Nettis MA, Lawrence A, Riley R, van der Windt D. Study protocol for the development and internal validation of Schizophrenia Prediction of Resistance to Treatment (SPIRIT): a clinical tool for predicting risk of treatment resistance to antipsychotics in first-episode schizophrenia. BMJ Open 2022; 12:e056420. [PMID: 35396294 PMCID: PMC8996048 DOI: 10.1136/bmjopen-2021-056420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 03/16/2022] [Indexed: 11/30/2022] Open
Abstract
INTRODUCTION Treatment-resistant schizophrenia (TRS) is associated with significant impairment of functioning and high treatment costs. Identification of patients at high risk of TRS at the time of their initial diagnosis may significantly improve clinical outcomes and minimise social and functional disability. We aim to develop a prognostic model for predicting the risk of developing TRS in patients with first-episode schizophrenia and to examine its potential utility and acceptability as a clinical decision tool. METHODS AND ANALYSIS We will use two well-characterised longitudinal UK-based first-episode psychosis cohorts: Aetiology and Ethnicity in Schizophrenia and Other Psychoses and Genetics and Psychosis for which data have been collected on sociodemographic and clinical characteristics. We will identify candidate predictors for the model based on current literature and stakeholder consultation. Model development will use all data, with the number of candidate predictors restricted according to available sample size and event rate. A model for predicting risk of TRS will be developed based on penalised regression, with missing data handled using multiple imputation. Internal validation will be undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. The clinical utility of the model in terms of clinically relevant risk thresholds will be evaluated using net benefit and decision curves (comparative to competing strategies). Consultation with patients and clinical stakeholders will determine potential thresholds of risk for treatment decision-making. The acceptability of embedding the model as a clinical tool will be explored using qualitative focus groups with up to 20 clinicians in total from early intervention services. Clinicians will be recruited from services in Stafford and London with the focus groups being held via an online platform. ETHICS AND DISSEMINATION The development of the prognostic model will be based on anonymised data from existing cohorts, for which ethical approval is in place. Ethical approval has been obtained from Keele University for the qualitative focus groups within early intervention in psychosis services (ref: MH-210174). Suitable processes are in place to obtain informed consent for National Health Service staff taking part in interviews or focus groups. A study information sheet with cover letter and consent form have been prepared and approved by the local Research Ethics Committee. Findings will be shared through peer-reviewed publications, conference presentations and social media. A lay summary will be published on collaborator websites.
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Affiliation(s)
- Saeed Farooq
- Midlands Partnership NHS Foundation Trust, Stafford, Staffordshire, UK
- School of Medicine, Keele University, Keele, Staffordshire, UK
| | - Miriam Hattle
- School of Medicine, Keele University, Keele, Staffordshire, UK
| | - Paola Dazzan
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Tom Kingstone
- Midlands Partnership NHS Foundation Trust, Stafford, Staffordshire, UK
- School of Medicine, Keele University, Keele, Staffordshire, UK
| | - Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - David Shiers
- School of Medicine, Keele University, Keele, Staffordshire, UK
- Psychosis Research Unit, Greater Manchester Mental Health NHS Trust, Manchester, UK
- Division of Psychology and Mental Health, University of Manchester, Manchester, UK
| | - Maria Antonietta Nettis
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, University of London, London, UK
| | - Andrew Lawrence
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, University of London, London, UK
| | - Richard Riley
- School of Medicine, Keele University, Keele, Staffordshire, UK
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27
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Okhuijsen-Pfeifer C, van der Horst MZ, Bousman CA, Lin B, van Eijk KR, Ripke S, Ayhan Y, Babaoglu MO, Bak M, Alink W, van Beek H, Beld E, Bouhuis A, Edlinger M, Erdogan IM, Ertuğrul A, Yoca G, Everall IP, Görlitz T, Grootens KP, Gutwinski S, Hallikainen T, Jeger-Land E, de Koning M, Lähteenvuo M, Legge SE, Leucht S, Morgenroth C, Müderrisoğlu A, Narang A, Pantelis C, Pardiñas AF, Oviedo-Salcedo T, Schneider-Thoma J, Schreiter S, Repo-Tiihonen E, Tuppurainen H, Veereschild M, Veerman S, de Vos M, Wagner E, Cohen D, Bogers JPAM, Walters JTR, Yağcıoğlu AEA, Tiihonen J, Hasan A, Luykx JJ. Genome-wide association analyses of symptom severity among clozapine-treated patients with schizophrenia spectrum disorders. Transl Psychiatry 2022; 12:145. [PMID: 35393395 PMCID: PMC8989876 DOI: 10.1038/s41398-022-01884-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 02/24/2022] [Accepted: 03/07/2022] [Indexed: 12/26/2022] Open
Abstract
Clozapine is the most effective antipsychotic for patients with treatment-resistant schizophrenia. However, response is highly variable and possible genetic underpinnings of this variability remain unknown. Here, we performed polygenic risk score (PRS) analyses to estimate the amount of variance in symptom severity among clozapine-treated patients explained by PRSs (R2) and examined the association between symptom severity and genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activity. Genome-wide association (GWA) analyses were performed to explore loci associated with symptom severity. A multicenter cohort of 804 patients (after quality control N = 684) with schizophrenia spectrum disorder treated with clozapine were cross-sectionally assessed using the Positive and Negative Syndrome Scale and/or the Clinical Global Impression-Severity (CGI-S) scale. GWA and PRS regression analyses were conducted. Genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activities were calculated. Schizophrenia-PRS was most significantly and positively associated with low symptom severity (p = 1.03 × 10-3; R2 = 1.85). Cross-disorder-PRS was also positively associated with lower CGI-S score (p = 0.01; R2 = 0.81). Compared to the lowest tertile, patients in the highest schizophrenia-PRS tertile had 1.94 times (p = 6.84×10-4) increased probability of low symptom severity. Higher genotype-predicted CYP2C19 enzyme activity was independently associated with lower symptom severity (p = 8.44×10-3). While no locus surpassed the genome-wide significance threshold, rs1923778 within NFIB showed a suggestive association (p = 3.78×10-7) with symptom severity. We show that high schizophrenia-PRS and genotype-predicted CYP2C19 enzyme activity are independently associated with lower symptom severity among individuals treated with clozapine. Our findings open avenues for future pharmacogenomic projects investigating the potential of PRS and genotype-predicted CYP-activity in schizophrenia.
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Affiliation(s)
- C Okhuijsen-Pfeifer
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center, Utrecht, The Netherlands
- Department of Translational Neuroscience, University Medical Center Utrecht, Utrecht University, Brain Center, Utrecht, The Netherlands
| | - M Z van der Horst
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center, Utrecht, The Netherlands
- Department of Translational Neuroscience, University Medical Center Utrecht, Utrecht University, Brain Center, Utrecht, The Netherlands
- GGNet Mental Health, Warnsveld, The Netherlands
| | - C A Bousman
- Department of Medical Genetics, University of Calgary, Calgary, Canada
- Department of Psychiatry, University of Calgary, Calgary, Canada
- Department of Physiology & Pharmacology, University of Calgary, Calgary, Canada
- Department of Psychiatry, University of Melbourne, Melbourne Neuropsychiatry Centre, Melbourne, Australia
| | - B Lin
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center, Utrecht, The Netherlands
- Department of Translational Neuroscience, University Medical Center Utrecht, Utrecht University, Brain Center, Utrecht, The Netherlands
| | - K R van Eijk
- Department of Translational Neuroscience, University Medical Center Utrecht, Utrecht University, Brain Center, Utrecht, The Netherlands
| | - S Ripke
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Berlin, Germany
| | - Y Ayhan
- Department of Psychiatry, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - M O Babaoglu
- Department of Pharmacology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - M Bak
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
- Mondriaan, Mental Health Institute, Maastricht, The Netherlands
| | - W Alink
- Multicomplexe Zorg, Pro Persona, Wolfheze, The Netherlands
| | - H van Beek
- Clinical Recovery Clinic, Mental Health Services Rivierduinen, Leiden, The Netherlands
| | - E Beld
- Mental Health Organization North-Holland North location Den Helder, Den Helder, The Netherlands
| | - A Bouhuis
- Program for early psychosis & severe mental illness, Pro Persona Mental Healthcare, Wolfheze, The Netherlands
| | - M Edlinger
- Department of Psychiatry, Psychotherapy and Psychosomatics, Division for Psychiatry I, Medical University Innsbruck, Innsbruck, Austria
| | - I M Erdogan
- Department of Psychiatry, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - A Ertuğrul
- Department of Psychiatry, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - G Yoca
- Department of Psychiatry, Faculty of Medicine, Hacettepe University, Ankara, Turkey
- Şarkışla State Hospital, Ministry of Health, Sivas, Turkey
| | - I P Everall
- Department of Psychiatry, University of Melbourne, Melbourne Neuropsychiatry Centre, Melbourne, Australia
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - T Görlitz
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty University Augsburg, Bezirkskrankenhaus Augsburg, Augsburg, Germany
| | - K P Grootens
- Reinier van Arkel, s-Hertogenbosch, The Netherlands
- Unit for Clinical Psychopharmacology and Neuropsychiatry, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - S Gutwinski
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Berlin, Germany
| | - T Hallikainen
- Department of Forensic Psychiatry, University of Kuopio, Niuvanniemi Hospital, Kuopio, Finland
| | - E Jeger-Land
- Arkin, Institute for Mental Health, Amsterdam, The Netherlands
| | - M de Koning
- Arkin, Institute for Mental Health, Amsterdam, The Netherlands
- Amsterdam UMC, University of Amsterdam, Department of Psychiatry, Amsterdam, The Netherlands
| | - M Lähteenvuo
- Department of Forensic Psychiatry, University of Kuopio, Niuvanniemi Hospital, Kuopio, Finland
| | - S E Legge
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - S Leucht
- Department of Psychiatry and Psychotherapy, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - C Morgenroth
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Berlin, Germany
| | - A Müderrisoğlu
- Department of Pharmacology, Faculty of Medicine, Kırıkkale University, Kırıkkale, Turkey
| | - A Narang
- Department of Medical Genetics, University of Calgary, Calgary, Canada
| | - C Pantelis
- Department of Psychiatry, University of Melbourne, Melbourne Neuropsychiatry Centre, Melbourne, Australia
| | - A F Pardiñas
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - T Oviedo-Salcedo
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - J Schneider-Thoma
- Department of Psychiatry and Psychotherapy, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - S Schreiter
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Berlin, Germany
- Berlin Institute of Health (BIH), BIH Biomedical Innovation Academy, Berlin, Germany
| | - E Repo-Tiihonen
- Department of Forensic Psychiatry, University of Kuopio, Niuvanniemi Hospital, Kuopio, Finland
| | - H Tuppurainen
- Department of Forensic Psychiatry, University of Kuopio, Niuvanniemi Hospital, Kuopio, Finland
| | | | - S Veerman
- Mental Health Organization North-Holland North location Alkmaar, Alkmaar, The Netherlands
| | - M de Vos
- GGNet Mental Health, Warnsveld, The Netherlands
| | - E Wagner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - D Cohen
- Mental Health Organization North-Holland North location Heerhugowaard, Heerhugowaard, The Netherlands
| | - J P A M Bogers
- High Care Clinics, Mental Health Services Rivierduinen, Leiden, The Netherlands
| | - J T R Walters
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - A E Anil Yağcıoğlu
- Department of Psychiatry, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - J Tiihonen
- Department of Forensic Psychiatry, University of Kuopio, Niuvanniemi Hospital, Kuopio, Finland
- Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
- Center for Psychiatric Research, Stockholm City Council, Stockholm, Sweden
| | - A Hasan
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty University Augsburg, Bezirkskrankenhaus Augsburg, Augsburg, Germany
| | - J J Luykx
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center, Utrecht, The Netherlands.
- Department of Translational Neuroscience, University Medical Center Utrecht, Utrecht University, Brain Center, Utrecht, The Netherlands.
- GGNet Mental Health, Warnsveld, The Netherlands.
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28
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Talarico F, Costa GO, Ota VK, Santoro ML, Noto C, Gadelha A, Bressan R, Azevedo H, Belangero SI. Systems-Level Analysis of Genetic Variants Reveals Functional and Spatiotemporal Context in Treatment-resistant Schizophrenia. Mol Neurobiol 2022; 59:3170-3182. [DOI: 10.1007/s12035-022-02794-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/06/2022] [Indexed: 10/18/2022]
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Pardiñas AF, Smart SE, Willcocks IR, Holmans PA, Dennison CA, Lynham AJ, Legge SE, Baune BT, Bigdeli TB, Cairns MJ, Corvin A, Fanous AH, Frank J, Kelly B, McQuillin A, Melle I, Mortensen PB, Mowry BJ, Pato CN, Periyasamy S, Rietschel M, Rujescu D, Simonsen C, St Clair D, Tooney P, Wu JQ, Andreassen OA, Kowalec K, Sullivan PF, Murray RM, Owen MJ, MacCabe JH, O’Donovan MC, Walters JTR, Ajnakina O, Alameda L, Barnes TRE, Berardi D, Bonora E, Camporesi S, Cleusix M, Conus P, Crespo-Facorro B, D'Andrea G, Demjaha A, Do KQ, Doody GA, Eap CB, Ferchiou A, Di Forti M, Guidi L, Homman L, Jenni R, Joyce EM, Kassoumeri L, Khadimallah I, Lastrina O, Muratori R, Noyan H, O'Neill FA, Pignon B, Restellini R, Richard JR, Schürhoff F, Španiel F, Szöke A, Tarricone I, Tortelli A, Üçok A, Vázquez-Bourgon J. Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia. JAMA Psychiatry 2022; 79:260-269. [PMID: 35019943 PMCID: PMC8756361 DOI: 10.1001/jamapsychiatry.2021.3799] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
IMPORTANCE About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. OBJECTIVE To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. DESIGN, SETTING, AND PARTICIPANTS Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). MAIN OUTCOMES AND MEASURES GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. RESULTS The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04). CONCLUSIONS AND RELEVANCE In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.
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Affiliation(s)
- Antonio F. Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Sophie E. Smart
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom,Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Isabella R. Willcocks
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Peter A. Holmans
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Charlotte A. Dennison
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Amy J. Lynham
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Sophie E. Legge
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Bernhard T. Baune
- Department of Psychiatry, University of Münster, Münster, Germany,Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Australia,The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
| | - Tim B. Bigdeli
- Department of Psychiatry and the Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn,Institute for Genomic Health, State University of New York Downstate Medical Center, Brooklyn,Department of Psychiatry, Veterans Affairs New York Harbor Healthcare System, Brooklyn
| | - Murray J. Cairns
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia,Centre for Brain and Mental Health Research, University of Newcastle, Newcastle, Australia,Hunter Medical Research Institute, Newcastle, Australia
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Ayman H. Fanous
- Department of Psychiatry and the Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn,Institute for Genomic Health, State University of New York Downstate Medical Center, Brooklyn
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Mannheim, Germany
| | - Brian Kelly
- School of Medicine & Public Health, The University of Newcastle, Newcastle, Australia
| | - Andrew McQuillin
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, United Kingdom
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, Oslo, Norway
| | - Preben B. Mortensen
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark,The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
| | - Bryan J. Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia,Queensland Centre for Mental Health Research, The University of Queensland, Brisbane, Australia
| | - Carlos N. Pato
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn,Department of Psychiatry and Zilkha Neurogenetics Institute, Keck School of Medicine, University of Southern California, Los Angeles,Institute for Genomic Health, State University of New York Downstate Medical Center, Brooklyn
| | - Sathish Periyasamy
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia,Queensland Centre for Mental Health Research, The University of Queensland, Brisbane, Australia
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Mannheim, Germany
| | - Dan Rujescu
- University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Martin Luther University of Halle-Wittenberg, Halle, Germany,Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Carmen Simonsen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Early Intervention in Psychosis Advisory Unit for South-East Norway, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - David St Clair
- Institute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Paul Tooney
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia,Hunter Medical Research Institute, Newcastle, Australia
| | - Jing Qin Wu
- Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital, Oslo, Norway
| | - Kaarina Kowalec
- College of Pharmacy, University of Manitoba, Winnipeg, Manitoba, Canada,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrick F. Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,Department of Psychiatry, Icahn School of Medicine, Mount Sinai Hospital, New York, New York,Department of Genetics, University of North Carolina, Chapel Hill
| | - Robin M. Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Michael J. Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - James H. MacCabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Michael C. O’Donovan
- MRC 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
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | | | - Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, University of London, London, United Kingdom.,Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Luis Alameda
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.,Centro de Investigacion Biomedica en Red de Salud Mental, Spanish Network for Research in Mental Health, Sevilla, Spain.,Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio, Departamento de Psiquiatria, Universidad de Sevilla, Sevilla, Spain.,Treatment and Early Intervention in Psychosis Program, Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Thomas R E Barnes
- Division of Psychiatry, Imperial College London, London, United Kingdom
| | - Domenico Berardi
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Elena Bonora
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Sara Camporesi
- Treatment and Early Intervention in Psychosis Program, Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland.,Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Martine Cleusix
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Philippe Conus
- Treatment and Early Intervention in Psychosis Program, Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Benedicto Crespo-Facorro
- Centro de Investigacion Biomedica en Red de Salud Mental, Spanish Network for Research in Mental Health, Sevilla, Spain.,Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocio, Departamento de Psiquiatria, Universidad de Sevilla, Sevilla, Spain
| | - Giuseppe D'Andrea
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Arsime Demjaha
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Kim Q Do
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Gillian A Doody
- Department of Medical Education, University of Nottingham Faculty of Medicine and Health Sciences, Nottingham, United Kingdom
| | - Chin B Eap
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Aziz Ferchiou
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France
| | - Marta Di Forti
- Social Genetics and Developmental Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.,South London and Maudsley National Health Service Mental Health Foundation Trust, London, United Kingdom
| | - Lorenzo Guidi
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Lina Homman
- Department of Social and Welfare Studies, Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden.,Centre For Public Health, Institute Of Clinical Sciences, Queens University Belfast, Belfast, United Kingdom
| | - Raoul Jenni
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Eileen M Joyce
- UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Laura Kassoumeri
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Inès Khadimallah
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Ornella Lastrina
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Roberto Muratori
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Handan Noyan
- Faculty of Social Sciences, Department of Psychology, Beykoz University, Istanbul, Turkey
| | - Francis A O'Neill
- Centre For Public Health, Institute Of Clinical Sciences, Queens University Belfast, Belfast, United Kingdom
| | - Baptiste Pignon
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires HMondor, Département Médico-Universitaire de Psychiatrie et d'Addictologie, Fédération Hospitalo-Universitaire de Médecine de Précision, Créteil, France
| | - Romeo Restellini
- Treatment and Early Intervention in Psychosis Program, Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland.,Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Jean-Romain Richard
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France
| | - Franck Schürhoff
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires HMondor, Département Médico-Universitaire de Psychiatrie et d'Addictologie, Fédération Hospitalo-Universitaire de Médecine de Précision, Créteil, France
| | - Filip Španiel
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia.,Department of Psychiatry and Medical Psychology, Third Faculty of Medicine, Charles University, Prague, Czechia
| | - Andrei Szöke
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires HMondor, Département Médico-Universitaire de Psychiatrie et d'Addictologie, Fédération Hospitalo-Universitaire de Médecine de Précision, Créteil, France
| | - Ilaria Tarricone
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Andrea Tortelli
- University Paris-Est Créteil, Institut national de la santé et de la recherche médicale, Mondor Institute for Biomedical Research, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Groupe Hospitalier Universitaire Psychiatrie Neurosciences Paris, Pôle Psychiatrie Précarité, Paris, France
| | - Alp Üçok
- Department of Psychiatry, Istanbul University, Istanbul, Turkey
| | - Javier Vázquez-Bourgon
- Department of Psychiatry, University Hospital Marques de Valdecilla-Instituto de Investigación Marques de Valdecilla, Santander, Spain.,Department of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander, Spain.,Centro de Investigacion Biomedica en Red de Salud Mental, Spanish Network for Research in Mental Health, Santander, Spain
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30
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Giangrande EJ, Weber RS, Turkheimer E. What Do We Know About the Genetic Architecture of Psychopathology? Annu Rev Clin Psychol 2022; 18:19-42. [DOI: 10.1146/annurev-clinpsy-081219-091234] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
In the second half of the twentieth century, twin and family studies established beyond a reasonable doubt that all forms of psychopathology are substantially heritable and highly polygenic. These conclusions were simultaneously an important theoretical advance and a difficult methodological obstacle, as it became clear that heritability is universal and undifferentiated across forms of psychopathology, and the radical polygenicity of genetic effects limits the biological insight provided by genetically informed studies at the phenotypic level. The paradigm-shifting revolution brought on by the Human Genome Project has recapitulated the great methodological promise and the profound theoretical difficulties of the twin study era. We review these issues using the rubric of genetic architecture, which we define as a search for specific genetic insight that adds to the general conclusion that psychopathology is heritable and polygenic. Although significant problems remain, we see many promising avenues for progress. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Evan J. Giangrande
- Department of Psychology, University of Virginia, Charlottesville, Virginia, USA
| | - Ramona S. Weber
- Department of Psychology, University of Virginia, Charlottesville, Virginia, USA
| | - Eric Turkheimer
- Department of Psychology, University of Virginia, Charlottesville, Virginia, USA
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Treatment resistance in psychiatry: state of the art and new directions. Mol Psychiatry 2022; 27:58-72. [PMID: 34257409 PMCID: PMC8960394 DOI: 10.1038/s41380-021-01200-3] [Citation(s) in RCA: 114] [Impact Index Per Article: 57.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 05/26/2021] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
Treatment resistance affects 20-60% of patients with psychiatric disorders; and is associated with increased healthcare burden and costs up to ten-fold higher relative to patients in general. Whilst there has been a recent increase in the proportion of psychiatric research focussing on treatment resistance (R2 = 0.71, p < 0.0001), in absolute terms this is less than 1% of the total output and grossly out of proportion to its prevalence and impact. Here, we provide an overview of treatment resistance, considering its conceptualisation, assessment, epidemiology, impact, and common neurobiological models. We also review new treatments in development and future directions. We identify 23 consensus guidelines on its definition, covering schizophrenia, major depressive disorder, bipolar affective disorder, and obsessive compulsive disorder (OCD). This shows three core components to its definition, but also identifies heterogeneity and lack of criteria for a number of disorders, including panic disorder, post-traumatic stress disorder, and substance dependence. We provide a reporting check-list to aid comparisons across studies. We consider the concept of pseudo-resistance, linked to poor adherence or other factors, and provide an algorithm for the clinical assessment of treatment resistance. We identify nine drugs and a number of non-pharmacological approaches being developed for treatment resistance across schizophrenia, major depressive disorder, bipolar affective disorder, and OCD. Key outstanding issues for treatment resistance include heterogeneity and absence of consensus criteria, poor understanding of neurobiology, under-investment, and lack of treatments. We make recommendations to address these issues, including harmonisation of definitions, and research into the mechanisms and novel interventions to enable targeted and personalised therapeutic approaches.
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Cross B, Turner R, Pirmohamed M. Polygenic risk scores: An overview from bench to bedside for personalised medicine. Front Genet 2022; 13:1000667. [PMID: 36437929 PMCID: PMC9692112 DOI: 10.3389/fgene.2022.1000667] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 10/24/2022] [Indexed: 11/13/2022] Open
Abstract
Since the first polygenic risk score (PRS) in 2007, research in this area has progressed significantly. The increasing number of SNPs that have been identified by large scale GWAS analyses has fuelled the development of a myriad of PRSs for a wide variety of diseases and, more recently, to PRSs that potentially identify differential response to specific drugs. PRSs constitute a composite genomic biomarker and potential applications for PRSs in clinical practice encompass risk prediction and disease screening, early diagnosis, prognostication, and drug stratification to improve efficacy or reduce adverse drug reactions. Nevertheless, to our knowledge, no PRSs have yet been adopted into routine clinical practice. Beyond the technical considerations of PRS development, the major challenges that face PRSs include demonstrating clinical utility and circumnavigating the implementation of novel genomic technologies at scale into stretched healthcare systems. In this review, we discuss progress in developing disease susceptibility PRSs across multiple medical specialties, development of pharmacogenomic PRSs, and future directions for the field.
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Affiliation(s)
- Benjamin Cross
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Richard Turner
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Munir Pirmohamed
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
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Hirschfeldova K, Cerny J, Bozikova P, Kuchtiak V, Rausch T, Benes V, Spaniel F, Gregus D, Horacek J, Vyklicky L, Balik A. Evidence for the Association between the Intronic Haplotypes of Ionotropic Glutamate Receptors and First-Episode Schizophrenia. J Pers Med 2021; 11:1250. [PMID: 34945722 PMCID: PMC8708351 DOI: 10.3390/jpm11121250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/14/2021] [Accepted: 11/16/2021] [Indexed: 11/16/2022] Open
Abstract
The heritable component of schizophrenia (SCH) as a polygenic trait is represented by numerous variants from a heterogeneous group of genes each contributing a relatively small effect. Various SNPs have already been found and analyzed in genes encoding the NMDAR subunits. However, less is known about genetic variations of genes encoding the AMPA and kainate receptor subunits. We analyzed sixteen iGluR genes in full length to determine the sequence variability of iGluR genes. Our aim was to describe the rate of genetic variability, its distribution, and the co-occurrence of variants and to identify new candidate risk variants or haplotypes. The cumulative effect of genetic risk was then estimated using a simple scoring model. GRIN2A-B, GRIN3A-B, and GRIK4 genes showed significantly increased genetic variation in SCH patients. The fixation index statistic revealed eight intronic haplotypes and an additional four intronic SNPs within the sequences of iGluR genes associated with SCH (p < 0.05). The haplotypes were used in the proposed simple scoring model and moreover as a test for genetic predisposition to schizophrenia. The positive likelihood ratio for the scoring model test reached 7.11. We also observed 41 protein-altering variants (38 missense variants, four frameshifts, and one nonsense variant) that were not significantly associated with SCH. Our data suggest that some intronic regulatory regions of iGluR genes and their common variability are among the components from which the genetic predisposition to SCH is composed.
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Affiliation(s)
- Katerina Hirschfeldova
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, 12800 Prague, Czech Republic;
- Institute of Physiology, Czech Academy of Sciences, 14220 Prague, Czech Republic; (J.C.); (V.K.); (L.V.)
| | - Jiri Cerny
- Institute of Physiology, Czech Academy of Sciences, 14220 Prague, Czech Republic; (J.C.); (V.K.); (L.V.)
- Institute of Biotechnology, Czech Academy of Sciences, BIOCEV, 25250 Vestec, Czech Republic;
| | - Paulina Bozikova
- Institute of Biotechnology, Czech Academy of Sciences, BIOCEV, 25250 Vestec, Czech Republic;
| | - Viktor Kuchtiak
- Institute of Physiology, Czech Academy of Sciences, 14220 Prague, Czech Republic; (J.C.); (V.K.); (L.V.)
- Faculty of Science, Charles University, 12800 Prague, Czech Republic
| | - Tobias Rausch
- Genomics Core Facility, EMBL, 69117 Heidelberg, Germany; (T.R.); (V.B.)
| | - Vladimir Benes
- Genomics Core Facility, EMBL, 69117 Heidelberg, Germany; (T.R.); (V.B.)
| | - Filip Spaniel
- The National Institute of Mental Health, 25067 Klecany, Czech Republic; (F.S.); (D.G.); (J.H.)
| | - David Gregus
- The National Institute of Mental Health, 25067 Klecany, Czech Republic; (F.S.); (D.G.); (J.H.)
| | - Jiri Horacek
- The National Institute of Mental Health, 25067 Klecany, Czech Republic; (F.S.); (D.G.); (J.H.)
| | - Ladislav Vyklicky
- Institute of Physiology, Czech Academy of Sciences, 14220 Prague, Czech Republic; (J.C.); (V.K.); (L.V.)
| | - Ales Balik
- Institute of Physiology, Czech Academy of Sciences, 14220 Prague, Czech Republic; (J.C.); (V.K.); (L.V.)
- Institute of Physiology, Czech Academy of Sciences, BIOCEV, 25250 Vestec, Czech Republic
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34
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Krebs MD, Themudo GE, Benros ME, Mors O, Børglum AD, Hougaard D, Mortensen PB, Nordentoft M, Gandal MJ, Fan CC, Geschwind DH, Schork AJ, Werge T, Thompson WK. Associations between patterns in comorbid diagnostic trajectories of individuals with schizophrenia and etiological factors. Nat Commun 2021; 12:6617. [PMID: 34785645 PMCID: PMC8595374 DOI: 10.1038/s41467-021-26903-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 10/15/2021] [Indexed: 12/26/2022] Open
Abstract
Schizophrenia is a heterogeneous disorder, exhibiting variability in presentation and outcomes that complicate treatment and recovery. To explore this heterogeneity, we leverage the comprehensive Danish health registries to conduct a prospective, longitudinal study from birth of 5432 individuals who would ultimately be diagnosed with schizophrenia, building individual trajectories that represent sequences of comorbid diagnoses, and describing patterns in the individual-level variability. We show that psychiatric comorbidity is prevalent among individuals with schizophrenia (82%) and multi-morbidity occur more frequently in specific, time-ordered pairs. Three latent factors capture 79% of variation in longitudinal comorbidity and broadly relate to the number of co-occurring diagnoses, the presence of child versus adult comorbidities and substance abuse. Clustering of the factor scores revealed five stable clusters of individuals, associated with specific risk factors and outcomes. The presentation and course of schizophrenia may be associated with heterogeneity in etiological factors including family history of mental disorders.
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Affiliation(s)
- Morten Dybdahl Krebs
- Institute of Biological Psychiatry, Mental Health Centre Sct Hans, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
| | - Gonçalo Espregueira Themudo
- Institute of Biological Psychiatry, Mental Health Centre Sct Hans, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
| | - Michael Eriksen Benros
- Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Immunology and Microbiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole Mors
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Aarhus University Hospital, Risskov, Denmark
| | - Anders D Børglum
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Department of Biomedicine and iSEQ-Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - David Hougaard
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Preben Bo Mortensen
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
- National Centre for Register-Based Research, Aarhus University, Business and Social Sciences, Aarhus, Denmark
| | - Merete Nordentoft
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Michael J Gandal
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Chun Chieh Fan
- Institute of Biological Psychiatry, Mental Health Centre Sct Hans, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Center for Human Development, University of California, San Diego, CA, USA
| | - Daniel H Geschwind
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Centre Sct Hans, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Centre Sct Hans, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark.
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.
- Center for GeoGenetics, Globe Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Wesley K Thompson
- Institute of Biological Psychiatry, Mental Health Centre Sct Hans, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Division of Biostatistics and Department of Radiology, Population Neuroscience and Genetics Lab, University of California, San Diego, CA, 92093, USA
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Legge SE, Santoro ML, Periyasamy S, Okewole A, Arsalan A, Kowalec K. Genetic architecture of schizophrenia: a review of major advancements. Psychol Med 2021; 51:2168-2177. [PMID: 33550997 DOI: 10.1017/s0033291720005334] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Schizophrenia is a severe psychiatric disorder with high heritability. Consortia efforts and technological advancements have led to a substantial increase in knowledge of the genetic architecture of schizophrenia over the past decade. In this article, we provide an overview of the current understanding of the genetics of schizophrenia, outline remaining challenges, and summarise future directions of research. World-wide collaborations have resulted in genome-wide association studies (GWAS) in over 56 000 schizophrenia cases and 78 000 controls, which identified 176 distinct genetic loci. The latest GWAS from the Psychiatric Genetics Consortium, available as a pre-print, indicates that 270 distinct common genetic loci have now been associated with schizophrenia. Polygenic risk scores can currently explain around 7.7% of the variance in schizophrenia case-control status. Rare variant studies have implicated eight rare copy-number variants, and an increased burden of loss-of-function variants in SETD1A, as increasing the risk of schizophrenia. The latest exome sequencing study, available as a pre-print, implicates a burden of rare coding variants in a further nine genes. Gene-set analyses have demonstrated significant enrichment of both common and rare genetic variants associated with schizophrenia in synaptic pathways. To address current challenges, future genetic studies of schizophrenia need increased sample sizes from more diverse populations. Continued expansion of international collaboration will likely identify new genetic regions, improve fine-mapping to identify causal variants, and increase our understanding of the biology and mechanisms of schizophrenia.
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Affiliation(s)
- Sophie E Legge
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Marcos L Santoro
- Departamento de Morfologia e Genética, Universidade Federal de Sao Paulo, Sao Paulo, Brazil
- Laboratory of Integrative Neuroscience, Departamento de Psiquiatria, Universidade Federal de Sao Paulo, Sao Paulo, Brazil
| | - Sathish Periyasamy
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
- Queensland Centre for Mental Health Research, The University of Queensland, Brisbane, QLD, Australia
| | | | - Arsalan Arsalan
- Department of Pharmacy, University of Peshawar, Peshawar, Pakistan
| | - Kaarina Kowalec
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- College of Pharmacy, University of Manitoba, Winnipeg, Canada
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Kowalec K, Lu Y, Sariaslan A, Song J, Ploner A, Dalman C, Hultman CM, Larsson H, Lichtenstein P, Sullivan PF. Increased schizophrenia family history burden and reduced premorbid IQ in treatment-resistant schizophrenia: a Swedish National Register and Genomic Study. Mol Psychiatry 2021; 26:4487-4495. [PMID: 31712719 PMCID: PMC9731609 DOI: 10.1038/s41380-019-0575-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 09/23/2019] [Accepted: 10/23/2019] [Indexed: 01/29/2023]
Abstract
A high proportion of those with schizophrenia experience treatment non-response, placing them at higher risk for mortality and suicide attempts, compared to treatment responders. The clinical, social, and economic burden of treatment-resistant schizophrenia (TRS) are substantial. Previous genomic and epidemiological studies of TRS were often limited by sample size or lack of comprehensive genomic data. We aimed to systematically understand the clinical, demographic, and genomic correlates of TRS using epidemiological and genetic epidemiological modelling in a Swedish national population sample (n = 24,706) and then in a subgroup with common variant genetic risk scores, rare copy-number variant burden, and rare exonic burden (n = 4936). Population-based analyses identified increasing schizophrenia family history to be significantly associated with TRS (highest quartile of familial burden vs. lowest: adjusted odds ratio (aOR): 1.31, P = 4.8 × 10-8). In males, a decrease of premorbid IQ of one standard deviation was significantly associated with greater risk of TRS (minimal aOR: 0.94, P = 0.002). In a subset of cases with extensive genomic data, we found no significant association between the genetic risk scores of four psychiatric disorders and two cognitive traits with TRS (schizophrenia genetic risk score: aOR = 1.07, P = 0.067). The association between copy number variant and rare variant burden measures and TRS did not reach the pre-defined statistical significance threshold (all P ≥ 0.005). In conclusion, direct measures of genomic risk were not associated with TRS; however, premorbid IQ in males and schizophrenia family history were significantly correlated with TRS and points to new insights into the architecture of TRS.
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Affiliation(s)
- Kaarina Kowalec
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, College of Pharmacy, University of Manitoba, Winnipeg, MB, Canada
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Amir Sariaslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jie Song
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Alexander Ploner
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Christina Dalman
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Christina M. Hultman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Icahn School of Medicine, Department of Psychiatry, Mt. Sinai Hospital, New York, NY, USA
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, School of Medical Sciences, Örebo University, Örebo, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrick F. Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Prakash J, Chatterjee K, Srivastava K, Chauhan VS. First-episode psychosis: How long does it last? A review of evolution and trajectory. Ind Psychiatry J 2021; 30:198-206. [PMID: 35017801 PMCID: PMC8709526 DOI: 10.4103/ipj.ipj_38_21] [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: 02/23/2021] [Revised: 03/13/2021] [Accepted: 03/16/2021] [Indexed: 11/12/2022] Open
Abstract
Study of first-episode psychosis (FEP), an episode of psychotic nature which manifests for the first time in an individual in the longitudinal continuum of his/her illness, has been study matter of research interest in recent years. A comprehensive review of the literature will help us understand the evolution and trajectory of this concept better. A literature review of available articles addressing the concept, phenomenology, evolution, identification, course, and outcome of FEP was done; the same was subsequently divided into broad topics for better clarity and analyzed. FEP constituted a clinical psychotic phenomenon with underlying significant heterogeneity in diagnosis, stability, course, and outcome. The study has attempted to view FEP both as horizontal spectrum across various diagnoses and longitudinally ranging from asymptomatic individual with unknown risk status to attenuated psychosis to multiple relapses/unremitting illness. Many risk and protective factors have been brought out with varying certainty ranging bio-psycho-social spectrum. Efforts have been made to calculate polygenic risk score based on genes involvement/sharing between various psychotic spectrum disorders; as well as biomarker panels to identify people at risk. FEP may prove to be an important concept to understand psychosis in general; without putting things into the diagnostic rubric. It may help understand multiple risk and protective factors for the course and outcome of psychotic illness and may clear the cloud to sharpen the evidence toward commonality and distinctiveness between various psychotic diagnoses in vogue for more comprehensive concept.
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Affiliation(s)
- Jyoti Prakash
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - K. Chatterjee
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - K. Srivastava
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - V. S. Chauhan
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
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38
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Gamón V, Hurtado I, Salazar-Fraile J, Sanfélix-Gimeno G. Treatment patterns and appropriateness of antipsychotic prescriptions in patients with schizophrenia. Sci Rep 2021; 11:13509. [PMID: 34188093 PMCID: PMC8241998 DOI: 10.1038/s41598-021-92731-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 06/14/2021] [Indexed: 02/06/2023] Open
Abstract
Schizophrenia is a chronic mental condition presenting a wide range of symptoms. Although it has a low prevalence compared to other mental conditions, it has a negative impact on social and occupational functions. This study aimed to assess the appropriateness of antipsychotic medications administered to schizophrenic patients and describe current treatment patterns for schizophrenia. A retrospective cohort study was conducted in all patients over the age of 15 with an active diagnosis of schizophrenia and treated with antipsychotics between 2008 and 2013 in the Valencia region. A total of 19,718 patients were eligible for inclusion. The main outcome assessed was inappropriateness of the pharmacotherapeutic management, including polypharmacy use. Altogether, 30.4% of patients received antipsychotic polypharmacy, and 6.8% were prescribed three or more antipsychotics. Overdosage affected 318 individuals (1.6%), and 21.5% used concomitant psychotropics without an associated psychiatric diagnosis. Women and people with a comorbid condition like anxiety or depression were less likely to receive antipsychotic polypharmacy. In contrast, increased polypharmacy was associated with concomitant treatment with other psychoactive drugs, and only in user on maintenance therapy, with more visits to the mental health hospital. Overall, we observed a high level of inappropriateness in antipsychotic prescriptions. Greater adherence to guidelines could maximize the benefits of antipsychotic medications while minimizing risk of adverse effects.
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Affiliation(s)
- Verónica Gamón
- Health Services Research Unit, Fundación Para el Fomento de La Investigación Sanitaria y Biomédica de la Comunidad Valenciana, FISABIO (the Valencia Foundation for the Promotion of Health and Biomedical Research), Valencia, Spain
| | - Isabel Hurtado
- Health Services Research Unit, Fundación Para el Fomento de La Investigación Sanitaria y Biomédica de la Comunidad Valenciana, FISABIO (the Valencia Foundation for the Promotion of Health and Biomedical Research), Valencia, Spain.
- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC, ), Valencia, Spain.
| | - José Salazar-Fraile
- Community Mental Health Centre Pere Bonfill, Valencia, Spain
- Consorcio Hospital General, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Valencia, Spain
| | - Gabriel Sanfélix-Gimeno
- Health Services Research Unit, Fundación Para el Fomento de La Investigación Sanitaria y Biomédica de la Comunidad Valenciana, FISABIO (the Valencia Foundation for the Promotion of Health and Biomedical Research), Valencia, Spain
- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC, ), Valencia, Spain
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39
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Lisoway AJ, Chen CC, Zai CC, Tiwari AK, Kennedy JL. Toward personalized medicine in schizophrenia: Genetics and epigenetics of antipsychotic treatment. Schizophr Res 2021; 232:112-124. [PMID: 34049235 DOI: 10.1016/j.schres.2021.05.010] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 04/30/2021] [Accepted: 05/02/2021] [Indexed: 12/21/2022]
Abstract
Schizophrenia is a complex psychiatric disorder where genetic, epigenetic, and environmental factors play a role in disease onset, course of illness, and treatment outcome. Pharmaco(epi)genetic research presents an important opportunity to improve patient care through prediction of medication side effects and response. In this narrative review, we discuss the current state of research and important progress of both genetic and epigenetic factors involved in antipsychotic response, over the past five years. The review is largely focused on the following frequently prescribed antipsychotics: olanzapine, risperidone, aripiprazole, and clozapine. Several consistent pharmacogenetic findings have emerged, in particular pharmacokinetic genes (primarily cytochrome P450 enzymes) and pharmacodynamic genes involving dopamine, serotonin, and glutamate neurotransmission. In addition to studies analysing DNA sequence variants, there are also several pharmacoepigenetic studies of antipsychotic response that have focused on the measurement of DNA methylation. Although pharmacoepigenetics is still in its infancy, consideration of both genetic and epigenetic factors contributing to antipsychotic response and side effects no doubt will be increasingly important in personalized medicine. We provide recommendations for next steps in research and clinical evaluation.
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Affiliation(s)
- Amanda J Lisoway
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada
| | - Cheng C Chen
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada
| | - Clement C Zai
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Canada; Department of Psychiatry, University of Toronto, Canada
| | - Arun K Tiwari
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Canada
| | - James L Kennedy
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada; Department of Psychiatry, University of Toronto, Canada.
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40
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Egerton A, Murphy A, Donocik J, Anton A, Barker GJ, Collier T, Deakin B, Drake R, Eliasson E, Emsley R, Gregory CJ, Griffiths K, Kapur S, Kassoumeri L, Knight L, Lambe EJB, Lawrie SM, Lees J, Lewis S, Lythgoe DJ, Matthews J, McGuire P, McNamee L, Semple S, Shaw AD, Singh KD, Stockton-Powdrell C, Talbot PS, Veronese M, Wagner E, Walters JTR, Williams SR, MacCabe JH, Howes OD. Dopamine and Glutamate in Antipsychotic-Responsive Compared With Antipsychotic-Nonresponsive Psychosis: A Multicenter Positron Emission Tomography and Magnetic Resonance Spectroscopy Study (STRATA). Schizophr Bull 2021; 47:505-516. [PMID: 32910150 PMCID: PMC7965076 DOI: 10.1093/schbul/sbaa128] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The variability in the response to antipsychotic medication in schizophrenia may reflect between-patient differences in neurobiology. Recent cross-sectional neuroimaging studies suggest that a poorer therapeutic response is associated with relatively normal striatal dopamine synthesis capacity but elevated anterior cingulate cortex (ACC) glutamate levels. We sought to test whether these measures can differentiate patients with psychosis who are antipsychotic responsive from those who are antipsychotic nonresponsive in a multicenter cross-sectional study. 1H-magnetic resonance spectroscopy (1H-MRS) was used to measure glutamate levels (Glucorr) in the ACC and in the right striatum in 92 patients across 4 sites (48 responders [R] and 44 nonresponders [NR]). In 54 patients at 2 sites (25 R and 29 NR), we additionally acquired 3,4-dihydroxy-6-[18F]fluoro-l-phenylalanine (18F-DOPA) positron emission tomography (PET) to index striatal dopamine function (Kicer, min-1). The mean ACC Glucorr was higher in the NR than the R group after adjustment for age and sex (F1,80 = 4.27; P = .04). This was associated with an area under the curve for the group discrimination of 0.59. There were no group differences in striatal dopamine function or striatal Glucorr. The results provide partial further support for a role of ACC glutamate, but not striatal dopamine synthesis, in determining the nature of the response to antipsychotic medication. The low discriminative accuracy might be improved in groups with greater clinical separation or increased in future studies that focus on the antipsychotic response at an earlier stage of the disorder and integrate other candidate predictive biomarkers. Greater harmonization of multicenter PET and 1H-MRS may also improve sensitivity.
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Affiliation(s)
- Alice Egerton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
| | - Anna Murphy
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Jacek Donocik
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Adriana Anton
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Academic Unit of Radiology, Medical School, Faculty of Medicine, Dentistry & Health, University of Sheffield, Sheffield, UK
| | - Gareth J Barker
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Tracy Collier
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
| | - Bill Deakin
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Richard Drake
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Emma Eliasson
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Richard Emsley
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Catherine J Gregory
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Kira Griffiths
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Shitij Kapur
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
- Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Laura Kassoumeri
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
| | - Laura Knight
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | - Emily J B Lambe
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | | | - Jane Lees
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Shôn Lewis
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - David J Lythgoe
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Julian Matthews
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
| | - Lily McNamee
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Scott Semple
- Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
| | - Alexander D Shaw
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | - Krish D Singh
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | - Charlotte Stockton-Powdrell
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Peter S Talbot
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Mattia Veronese
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Ernest Wagner
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Stephen R Williams
- Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, UK
| | - James H MacCabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, London, UK
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41
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Crouse JJ, Carpenter JS, Iorfino F, Lin T, Ho N, Byrne EM, Henders AK, Wallace L, Hermens DF, Scott EM, Wray NR, Hickie IB. Schizophrenia polygenic risk scores in youth mental health: preliminary associations with diagnosis, clinical stage and functioning. BJPsych Open 2021; 7:e58. [PMID: 33612137 PMCID: PMC8058892 DOI: 10.1192/bjo.2021.14] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The schizophrenia polygenic risk score (SCZ-PRS) is an emerging tool in psychiatry. AIMS We aimed to evaluate the utility of SCZ-PRS in a young, transdiagnostic, clinical cohort. METHOD SCZ-PRSs were calculated for young people who presented to early-intervention youth mental health clinics, including 158 patients of European ancestry, 113 of whom had longitudinal outcome data. We examined associations between SCZ-PRS and diagnosis, clinical stage and functioning at initial assessment, and new-onset psychotic disorder, clinical stage transition and functional course over time in contact with services. RESULTS Compared with a control group, patients had elevated PRSs for schizophrenia, bipolar disorder and depression, but not for any non-psychiatric phenotype (for example cardiovascular disease). Higher SCZ-PRSs were elevated in participants with psychotic, bipolar, depressive, anxiety and other disorders. At initial assessment, overall SCZ-PRSs were associated with psychotic disorder (odds ratio (OR) per s.d. increase in SCZ-PRS was 1.68, 95% CI 1.08-2.59, P = 0.020), but not assignment as clinical stage 2+ (i.e. discrete, persistent or recurrent disorder) (OR = 0.90, 95% CI 0.64-1.26, P = 0.53) or functioning (R = 0.03, P = 0.76). Longitudinally, overall SCZ-PRSs were not significantly associated with new-onset psychotic disorder (OR = 0.84, 95% CI 0.34-2.03, P = 0.69), clinical stage transition (OR = 1.02, 95% CI 0.70-1.48, P = 0.92) or persistent functional impairment (OR = 0.84, 95% CI 0.52-1.38, P = 0.50). CONCLUSIONS In this preliminary study, SCZ-PRSs were associated with psychotic disorder at initial assessment in a young, transdiagnostic, clinical cohort accessing early-intervention services. Larger clinical studies are needed to further evaluate the clinical utility of SCZ-PRSs, especially among individuals with high SCZ-PRS burden.
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Affiliation(s)
- Jacob J Crouse
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Australia
| | - Joanne S Carpenter
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Australia
| | - Frank Iorfino
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Australia
| | - Tian Lin
- Queensland Brain Institute, University of Queensland, Australia; and Institute of Molecular Bioscience, University of Queensland, Australia
| | - Nicholas Ho
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Australia
| | - Enda M Byrne
- Institute of Molecular Bioscience, University of Queensland, Australia
| | - Anjali K Henders
- Institute of Molecular Bioscience, University of Queensland, Australia
| | - Leanne Wallace
- Institute of Molecular Bioscience, University of Queensland, Australia
| | - Daniel F Hermens
- Sunshine Coast Mind and Neuroscience Thompson Institute, University of the Sunshine Coast, Australia
| | - Elizabeth M Scott
- St Vincent's and Mater Clinical School, The University of Notre Dame, Australia
| | - Naomi R Wray
- Queensland Brain Institute, University of Queensland, Australia; and Institute of Molecular Bioscience, University of Queensland, Australia
| | - Ian B Hickie
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Australia
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Smart SE, Kępińska AP, Murray RM, MacCabe JH. Predictors of treatment resistant schizophrenia: a systematic review of prospective observational studies. Psychol Med 2021; 51:44-53. [PMID: 31462334 PMCID: PMC7856410 DOI: 10.1017/s0033291719002083] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 06/24/2019] [Accepted: 07/25/2019] [Indexed: 12/29/2022]
Abstract
Treatment-resistant schizophrenia, affecting approximately 20-30% of patients with schizophrenia, has a high burden both for patients and healthcare services. There is a need to identify treatment resistance earlier in the course of the illness, in order that effective treatment, such as clozapine, can be offered promptly. We conducted a systemic literature review of prospective longitudinal studies with the aim of identifying predictors of treatment-resistant schizophrenia from the first episode. From the 545 results screened, we identified 12 published studies where data at the first episode was used to predict treatment resistance. Younger age of onset was the most consistent predictor of treatment resistance. We discuss the gaps in the literature and how future prediction models can identify predictors of treatment response more robustly.
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Affiliation(s)
- S. E. Smart
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, 16 de Crespigny Park, London, SE5 8AF, UK
| | - A. P. Kępińska
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, 16 de Crespigny Park, London, SE5 8AF, UK
| | - R. M. Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, 16 de Crespigny Park, London, SE5 8AF, UK
| | - J. H. MacCabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, 16 de Crespigny Park, London, SE5 8AF, UK
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Lanfear DE, Luzum JA, She R, Gui H, Donahue MP, O'Connor CM, Adams KF, Sanders-van Wijk S, Zeld N, Maeder MT, Sabbah HN, Kraus WE, Brunner-LaRocca HP, Li J, Williams LK. Polygenic Score for β-Blocker Survival Benefit in European Ancestry Patients With Reduced Ejection Fraction Heart Failure. Circ Heart Fail 2020; 13:e007012. [PMID: 33012170 DOI: 10.1161/circheartfailure.119.007012] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND β-Blockers (BBs) are mainstay therapy for heart failure with reduced ejection fraction. However, individual patient responses to BB vary, which may be partially due to genetic variation. The goal of this study was to derive and validate the first polygenic response predictor (PRP) for BB survival benefit in heart failure with reduced ejection fraction patients. METHODS Derivation and validation analyses were performed in n=1436 total HF patients of European descent and with ejection fraction <50%. The PRP was derived in a random subset of the Henry Ford Heart Failure Pharmacogenomic Registry (n=248) and then validated in a meta-analysis of the remaining patients from Henry Ford Heart Failure Pharmacogenomic Registry (n=247), the TIME-CHF (Trial of Intensified Versus Standard Medical Therapy in Elderly Patients With Congestive Heart Failure; n=431), and HF-ACTION trial (Heart Failure: a Controlled Trial Investigating Outcomes of Exercise Training; n=510). The PRP was constructed from a genome-wide analysis of BB×genotype interaction predicting time to all-cause mortality, adjusted for Meta-Analysis Global Group in Chronic Heart Failure score, genotype, level of BB exposure, and BB propensity score. RESULTS Five-fold cross-validation summaries out to 1000 single-nucleotide polymorphisms identified optimal prediction with a 44 single-nucleotide polymorphism score and cutoff at the 30th percentile. In validation testing (n=1188), greater BB exposure was associated with reduced all-cause mortality in patients with low PRP score (n=251; hazard ratio, 0.19 [95% CI, 0.04-0.51]; P=0.0075) but not high PRP score (n=937; hazard ratio, 0.84 [95% CI, 0.53-1.3]; P=0.448)-a difference that was statistically significant (P interaction, 0.0235). Results were consistent regardless of atrial fibrillation, ejection fraction (≤40% versus 41%-50%), or when examining cardiovascular death. CONCLUSIONS Among patients of European ancestry with heart failure with reduced ejection fraction, a PRP distinguished patients who derived substantial survival benefit from BB exposure from a larger group that did not. Additional work is needed to prospectively test clinical utility and to develop PRPs for other population groups and other medications.
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Affiliation(s)
- David E Lanfear
- Department of Internal Medicine, Center for Individualized and Genomic Medicine Research (D.E.L., J.A.L., R.S., H.G., N.Z., J.L., L.K.W.), Henry Ford Hospital, Detroit, MI.,Heart and Vascular Institute (D.E.L., H.N.S., J.L.), Henry Ford Hospital, Detroit, MI
| | - Jasmine A Luzum
- Department of Internal Medicine, Center for Individualized and Genomic Medicine Research (D.E.L., J.A.L., R.S., H.G., N.Z., J.L., L.K.W.), Henry Ford Hospital, Detroit, MI.,Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor (J.A.L.)
| | - Ruicong She
- Department of Internal Medicine, Center for Individualized and Genomic Medicine Research (D.E.L., J.A.L., R.S., H.G., N.Z., J.L., L.K.W.), Henry Ford Hospital, Detroit, MI.,Department of Public Health Sciences (R.S.), Henry Ford Hospital, Detroit, MI
| | - Hongsheng Gui
- Department of Internal Medicine, Center for Individualized and Genomic Medicine Research (D.E.L., J.A.L., R.S., H.G., N.Z., J.L., L.K.W.), Henry Ford Hospital, Detroit, MI
| | - Mark P Donahue
- Division of Cardiology, Duke University, Durham, NC (M.P.D., W.E.K.)
| | | | - Kirkwood F Adams
- Division of Cardiology, University of North Carolina, Chapel Hill (K.F.A.)
| | | | - Nicole Zeld
- Department of Internal Medicine, Center for Individualized and Genomic Medicine Research (D.E.L., J.A.L., R.S., H.G., N.Z., J.L., L.K.W.), Henry Ford Hospital, Detroit, MI
| | - Micha T Maeder
- Cardiology Department, Kantonsspital St. Gallen, Switzerland (M.T.M.)
| | - Hani N Sabbah
- Heart and Vascular Institute (D.E.L., H.N.S., J.L.), Henry Ford Hospital, Detroit, MI
| | - William E Kraus
- Division of Cardiology, Duke University, Durham, NC (M.P.D., W.E.K.)
| | | | - Jia Li
- Department of Internal Medicine, Center for Individualized and Genomic Medicine Research (D.E.L., J.A.L., R.S., H.G., N.Z., J.L., L.K.W.), Henry Ford Hospital, Detroit, MI.,Heart and Vascular Institute (D.E.L., H.N.S., J.L.), Henry Ford Hospital, Detroit, MI
| | - L Keoki Williams
- Department of Internal Medicine, Center for Individualized and Genomic Medicine Research (D.E.L., J.A.L., R.S., H.G., N.Z., J.L., L.K.W.), Henry Ford Hospital, Detroit, MI
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You X, Zhang Y, Long Q, Liu Z, Ma X, Lu Z, Yang W, Feng Z, Zhang W, Teng Z, Zeng Y. Investigating aberrantly expressed microRNAs in peripheral blood mononuclear cells from patients with treatment‑resistant schizophrenia using miRNA sequencing and integrated bioinformatics. Mol Med Rep 2020; 22:4340-4350. [PMID: 33000265 PMCID: PMC7533444 DOI: 10.3892/mmr.2020.11513] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 07/31/2020] [Indexed: 12/14/2022] Open
Abstract
Treatment-resistant schizophrenia (TRS) is a common phenotype of schizophrenia that places a considerable burden on patients as well as on society. TRS is known for its tendency to relapse and uncontrollable nature, with a poor response to antipsychotics other than clozapine. Therefore, it is urgent to identify objective biological markers, so as to guide its treatment and associated clinical work. In the present study, the peripheral blood mononuclear cells (PBMCs) of patients with TRS and a healthy control group, which were gender-, age- and ethnicity-matched, were subjected to microRNA (miRNA/miR) sequencing to screen out the top three miRNAs with the highest fold change values. These were then validated in the TRS (n=34) and healthy control (n=31) groups by reverse transcription-quantitative PCR. For two of the top three miRNAs, the PCR results were in accordance with the sequencing result (P<0.01), while the third miRNA exhibited the opposite trend (P<0.01). To elucidate the functions of these two miRNAs, Homo sapiens (hsa)-miR-218-5p and hsa-miR-1262 and their regulatory network, target gene prediction was first performed using online TargetScan and Diana-micro T software. Bioinformatics analysis was then performed using functional enrichment analysis to determine the Gene Ontology terms in the category biological process and the Kyoto Encyclopedia of Genes and Genomes pathways. It was revealed that these target genes were markedly associated with the nervous system and brain function, and it was obvious that the differentially expressed miRNAs most likely participated in the pathogenesis of TRS. A receiver operating characteristic curve was generated to confirm the distinct diagnostic value of these two miRNAs. It was concluded that aberrantly expressed miRNAs in PMBCs may be implicated in the pathogenesis of TRS and may serve as specific peripheral blood-based biomarkers for the early diagnosis of TRS.
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Affiliation(s)
- Xu You
- Research Management Department, The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, P.R. China
| | - Yunqiao Zhang
- Research Management Department, The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, P.R. China
| | - Qing Long
- Research Management Department, The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, P.R. China
| | - Zijun Liu
- Research Management Department, The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, P.R. China
| | - Xiao Ma
- Research Management Department, The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, P.R. China
| | - Zixiang Lu
- Psychiatric Ward, Honghe Second People's Hospital, Honghe, Yunnan 654399, P.R. China
| | - Wei Yang
- Psychiatric Ward, Yuxi Second People's Hospital, Yuxi, Yunnan 653100, P.R. China
| | - Ziqiao Feng
- Research Management Department, The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, P.R. China
| | - Wengyu Zhang
- Research Management Department, The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, P.R. China
| | - Zhaowei Teng
- Research Management Department, The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, P.R. China
| | - Yong Zeng
- Research Management Department, The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, P.R. China
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45
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Korth C, Fangerau H. Blood tests to diagnose schizophrenia: self-imposed limits in psychiatry. Lancet Psychiatry 2020; 7:911-914. [PMID: 32213327 DOI: 10.1016/s2215-0366(20)30058-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 02/02/2020] [Accepted: 02/04/2020] [Indexed: 11/26/2022]
Abstract
The naturalisation of mental disorders-ie, their translation into measurable and preferably molecular variables-has not progressed despite breath-taking discoveries in the neurosciences. We ask whether self-inflicted limits exist among psychiatrists that would prevent them from supporting an imaginary perfect blood test with diagnostic specificity, sensitivity, and validity, which was able to replace clinical diagnosis completely. Although relevant for many mental disorders, we use the clinical disease category schizophrenia here as an example to discuss factors that oppose the naturalisation of clinical disease categories. We defend the provocative position that a complete substitution of the clinical diagnosis by a blood test is generally not desired among clinicians because various factors perpetuate the current diagnostic culture. These are (1) methodological problems, such as a falsely presumed homogeneity of biological causes under the umbrella of one clinical diagnosis that prevents efficient subset identification, (2) professional fears, such as loss of importance of interview-diagnostic expert skills, and (3) conceptual problems, such as a dualistic mindset. We posit that doubts regarding the possibility of a blood test for diagnosing schizophrenia can subtly result in a negative self-fulfilling prophecy, discouraging serious scientific efforts to develop one. We give historical examples of how some of these problems have been solved in other medical disciplines. We predict that only blood tests that improve diagnostic accuracy but do not displace the primacy of clinical diagnosis will be successful. In the future, novel professional expertise for orchestrating various biological variables together with clinical criteria will be needed.
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Affiliation(s)
- Carsten Korth
- Institute of Neuropathology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| | - Heiner Fangerau
- Department of History, Philosophy, and Ethics of Medicine, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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46
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Lunenburg CATC, Gasse C. Pharmacogenetics in psychiatric care, a call for uptake of available applications. Psychiatry Res 2020; 292:113336. [PMID: 32739644 DOI: 10.1016/j.psychres.2020.113336] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 07/24/2020] [Accepted: 07/26/2020] [Indexed: 12/27/2022]
Abstract
In this narrative, we evaluate the role of pharmacogenetics in psychiatry from a pragmatic clinical perspective and address current barriers of clinical implementation of pharmacogenetics. Pharmacogenetics has been successfully implemented to improve drug therapy in several clinical areas, but not psychiatry. Yet, psychotropics account for more than one-third of the drugs for which pharmacogenetic guidelines are available and drug therapy in mental disorders is suboptimal with insufficient effectiveness and frequent adverse events. The limited application of pharmacogenetics in psychiatry is influenced by several factors; e.g. the complexity of psychotropic drug metabolism, possibly impeding the clinical understanding of the benefits of pharmacogenetics. Also, recommendations for most psychotropics classify pharmacogenetic testing only as (potentially) beneficial, not as essential, possibly because life-threatening adverse events are often not involved in these drug-gene interactions. Implementing pharmacogenetics in psychiatry could improve the current practice of time-consuming switching of therapies causing undue delays associated with worse outcomes. We expect pharmacogenetics in psychiatry to expedite with panel-based genotyping, including clinically relevant variants, which will address the complex enzymatic metabolism of psychotropic drugs. Until then, we stress that available pharmacogenetic testing should be seen as an integrated companion, not a competitor, in current clinical psychiatric care.
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Affiliation(s)
- Carin A T C Lunenburg
- Department of Affective Disorders, Aarhus University Hospital Psychiatry, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
| | - Christiane Gasse
- Department of Affective Disorders, Aarhus University Hospital Psychiatry, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark
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47
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Treble-Barna A, Pilipenko V, Wade SL, Jegga AG, Yeates KO, Taylor HG, Martin LJ, Kurowski BG. Cumulative Influence of Inflammatory Response Genetic Variation on Long-Term Neurobehavioral Outcomes after Pediatric Traumatic Brain Injury Relative to Orthopedic Injury: An Exploratory Polygenic Risk Score. J Neurotrauma 2020; 37:1491-1503. [PMID: 32024452 PMCID: PMC7307697 DOI: 10.1089/neu.2019.6866] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
The addition of genetic factors to prognostic models of neurobehavioral recovery following pediatric traumatic brain injury (TBI) may account for unexplained heterogeneity in outcomes. The present study examined the cumulative influence of candidate genes involved in the inflammatory response on long-term neurobehavioral recovery in children with early childhood TBI relative to children with orthopedic injuries (OI). Participants were drawn from a prospective, longitudinal study evaluating outcomes of children who sustained TBI (n = 67) or OI (n = 68) between the ages of 3 and 7 years. Parents completed ratings of child executive function and behavior at an average of 6.8 years after injury. Exploratory unweighted and weighted polygenic risk scores (PRS) were constructed from single nucleotide polymorphisms (SNPs) across candidate inflammatory response genes (i.e., angiotensin converting enzyme [ACE], brain-derived neurotrophic factor [BDNF], interleukin-1 receptor antagonist [IL1RN], and 5'-ectonucleotidase [NT5E]) that showed nominal (p ≤ 0.20) associations with outcomes in the TBI group. Linear regression models tested the PRS × injury group (TBI vs. OI) interaction term and post-hoc analyses examined the effect of PRS within each injury group. Higher inflammatory response PRS were associated with more executive dysfunction and behavior problems in children with TBI but not in children with OI. The cumulative influence of inflammatory response genes as measured by PRS explained additional variance in long-term neurobehavioral outcomes, over and above well-established predictors and single candidate SNPs tested individually. The results suggest that some of the unexplained heterogeneity in long-term neurobehavioral outcomes following pediatric TBI may be attributable to a child's genetic predisposition to a greater or lesser inflammatory response to TBI.
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Affiliation(s)
- Amery Treble-Barna
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, Pennslvania, USA
| | - Valentina Pilipenko
- Division of Human Genetics, Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Shari L. Wade
- Division of Pediatric Rehabilitation Medicine, Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Anil G. Jegga
- Division of Biomedical Informatics, Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Keith Owen Yeates
- Department of Psychology, Alberta Children's Hospital Research Institute, and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - H. Gerry Taylor
- Abigail Wexner Research Institute at Nationwide Children's Hospital, and Department of Pediatrics, The Ohio State University, Columbus, Ohio, USA
| | - Lisa J. Martin
- Division of Human Genetics, Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Brad G. Kurowski
- Division of Pediatric Rehabilitation Medicine, Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
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Legge SE, Dennison CA, Pardiñas AF, Rees E, Lynham AJ, Hopkins L, Bates L, Kirov G, Owen MJ, O'Donovan MC, Walters JTR. Clinical indicators of treatment-resistant psychosis. Br J Psychiatry 2020; 216:259-266. [PMID: 31155017 DOI: 10.1192/bjp.2019.120] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
BACKGROUND Around 30% of individuals with schizophrenia remain symptomatic and significantly impaired despite antipsychotic treatment and are considered to be treatment resistant. Clinicians are currently unable to predict which patients are at higher risk of treatment resistance. AIMS To determine whether genetic liability for schizophrenia and/or clinical characteristics measurable at illness onset can prospectively indicate a higher risk of treatment-resistant psychosis (TRP). METHOD In 1070 individuals with schizophrenia or related psychotic disorders, schizophrenia polygenic risk scores (PRS) and large copy number variations (CNVs) were assessed for enrichment in TRP. Regression and machine-learning approaches were used to investigate the association of phenotypes related to demographics, family history, premorbid factors and illness onset with TRP. RESULTS Younger age at onset (odds ratio 0.94, P = 7.79 × 10-13) and poor premorbid social adjustment (odds ratio 1.64, P = 2.41 × 10-4) increased risk of TRP in univariate regression analyses. These factors remained associated in multivariate regression analyses, which also found lower premorbid IQ (odds ratio 0.98, P = 7.76 × 10-3), younger father's age at birth (odds ratio 0.97, P = 0.015) and cannabis use (odds ratio 1.60, P = 0.025) increased the risk of TRP. Machine-learning approaches found age at onset to be the most important predictor and also identified premorbid IQ and poor social adjustment as predictors of TRP, mirroring findings from regression analyses. Genetic liability for schizophrenia was not associated with TRP. CONCLUSIONS People with an earlier age at onset of psychosis and poor premorbid functioning are more likely to be treatment resistant. The genetic architecture of susceptibility to schizophrenia may be distinct from that of treatment outcomes.
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Affiliation(s)
- Sophie E Legge
- Research Associate, Medical Research Council (MRC) Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - Charlotte A Dennison
- PhD Student, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - Antonio F Pardiñas
- Lecturer, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - Elliott Rees
- Research Associate, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - Amy J Lynham
- Research Associate, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - Lucinda Hopkins
- Sample and Governance Manager, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - Lesley Bates
- Laboratory Manager, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - George Kirov
- Professor, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - Michael J Owen
- Director, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - Michael C O'Donovan
- Professor, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
| | - James T R Walters
- Professor, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, UK
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Indicated association between polygenic risk score and treatment-resistance in a naturalistic sample of patients with schizophrenia spectrum disorders. Schizophr Res 2020; 218:55-62. [PMID: 32171635 DOI: 10.1016/j.schres.2020.03.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 03/02/2020] [Accepted: 03/05/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND One third of people diagnosed with schizophrenia fail to respond adequately to antipsychotic medication, resulting in persisting disabling symptoms, higher rates of hospitalization and higher costs for society. In an effort to better understand the mechanisms behind resistance to antipsychotic treatment in schizophrenia, we investigated its potential relationship to the genetic architecture of the disorder. METHODS Patients diagnosed with a schizophrenia spectrum disorder (N = 321) were classified as either being treatment-resistant (N = 108) or non-treatment-resistant (N = 213) to antipsychotic medication using defined consensus criteria. A schizophrenia polygenic risk score based on genome-wide association studies (GWAS) was calculated for each patient and binary logistic regression was performed to investigate the association between polygenetic risk and treatment resistance. We adjusted for principal components, batch number, age and sex. Additional analyses were performed to investigate associations with demographic and clinical variables. RESULTS High levels of polygenic risk score for schizophrenia significantly predicted treatment resistance (p = 0.003). The positive predictive value of the model was 61.5% and the negative predictive value was 71.7%. The association was significant for one (p = 0.01) out of five tested SNP significance thresholds. Season of birth was able to predict treatment-resistance in the regression model (p = 0.05). CONCLUSIONS The study indicates that treatment-resistance to antipsychotic medication is associated with higher polygenetic risk of schizophrenia, suggesting a link between antipsychotics mechanism of action and the genetic underpinnings of the disorder.
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50
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Dennison CA, Legge SE, Pardiñas AF, Walters JTR. Genome-wide association studies in schizophrenia: Recent advances, challenges and future perspective. Schizophr Res 2020; 217:4-12. [PMID: 31780348 DOI: 10.1016/j.schres.2019.10.048] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 10/24/2019] [Indexed: 01/07/2023]
Abstract
Genome-wide association studies (GWAS) have proved to be a powerful approach for gene discovery in schizophrenia; their findings have important implications not just for our understanding of the genetic architecture of the disorder, but for the potential applications of personalised medicine through improved classification and targeted interventions. In this article we review the current status of the GWAS literature in schizophrenia including functional annotation methods and polygenic risk scoring, as well as the directions and challenges of future research. We consider recent findings in East Asian populations and the advancements from trans-ancestry analysis, as well as the insights gained from research looking across psychiatric disorders.
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Affiliation(s)
- Charlotte A Dennison
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Sophie E Legge
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK.
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