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Koch E, Kämpe A, Alver M, Sigurðarson S, Einarsson G, Partanen J, Smith RL, Jaholkowski P, Taipale H, Lähteenvuo M, Steen NE, Smeland OB, Djurovic S, Molden E, Sigurdsson E, Stefánsson H, Stefánsson K, Palotie A, Milani L, O'Connell KS, Andreassen OA. Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study. Neuropsychopharmacology 2024; 49:1113-1119. [PMID: 38184734 PMCID: PMC11109158 DOI: 10.1038/s41386-023-01792-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 11/10/2023] [Accepted: 12/19/2023] [Indexed: 01/08/2024]
Abstract
Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.
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Affiliation(s)
- Elise Koch
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Anders Kämpe
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Maris Alver
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | | | - Juulia Partanen
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Robert L Smith
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
| | - Piotr Jaholkowski
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Heidi Taipale
- Niuvanniemi Hospital, Kuopio, Finland
- Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, Stockholm, Sweden
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | | | - Nils Eiel Steen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
- Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Engilbert Sigurdsson
- Faculty of Medicine, University of Iceland and Department of Psychiatry, Landspitali, National University Hospital, Reykjavík, Iceland
| | | | | | - Aarno Palotie
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Kevin S O'Connell
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway.
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Agid O, Crespo-Facorro B, de Bartolomeis A, Fagiolini A, Howes OD, Seppälä N, Correll CU. Overcoming the barriers to identifying and managing treatment-resistant schizophrenia and to improving access to clozapine: A narrative review and recommendation for clinical practice. Eur Neuropsychopharmacol 2024; 84:35-47. [PMID: 38657339 DOI: 10.1016/j.euroneuro.2024.04.012] [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: 02/05/2024] [Revised: 04/08/2024] [Accepted: 04/10/2024] [Indexed: 04/26/2024]
Abstract
Clozapine is the only approved antipsychotic for treatment-resistant schizophrenia (TRS). Although a large body of evidence supports its efficacy and favorable risk-benefit ratio in individuals who have failed two or more antipsychotics, clozapine remains underused. However, variations in clozapine utilization across geographic and clinical settings suggest that it could be possible to improve its use. In this narrative review and expert opinion, we summarized information available in the literature on the mechanisms of action, effectiveness, and potential adverse events of clozapine. We identified barriers leading to discouragement in clozapine prescription internationally, and we proposed practical solutions to overcome each barrier. One of the main obstacles identified to the use of clozapine is the lack of appropriate training for physicians: we highlighted the need to develop specific professional programs to train clinicians, both practicing and in residency, on the relevance and efficacy of clozapine in TRS treatment, initiation, maintenance, and management of potential adverse events. This approach would facilitate physicians to identify eligible patients and offer clozapine as a treatment option in the early stage of the disease. We also noted that increasing awareness of the benefits of clozapine among healthcare professionals, people with TRS, and their caregivers can help promote the use of clozapine. Educational material, such as leaflets or videos, could be developed and distributed to achieve this goal. The information provided in this article may be useful to improve disease burden and support healthcare professionals, patients, and caregivers navigating the complex pathways to TRS management.
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Affiliation(s)
- Ofer Agid
- Centre for Addiction and Mental Health, University of Toronto, Canada
| | - Benedicto Crespo-Facorro
- Department of Psychiatry, School of Medicine, University Hospital Virgen del Rocío-IBiS-CSIC, Sevilla, Spain, Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Sevilla, Spain
| | - Andrea de Bartolomeis
- University of Naples Federico II, Department of Neuroscience, Reproductive Science, and Odontostomatology. Laboratory of Molecular and Translational Psychiatry. Unit of Treatment Resistant Psychosis, Naples, Italy; Staff Unesco Chair at University of Naples Federico II, Italy
| | | | - Oliver D Howes
- IoPPN, King's College London, De Crespigny Park, London, United Kingdom; Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, Du Cane Road, London, United Kingdom
| | - Niko Seppälä
- Wellbeing Services in Satakunta, Department of Psychiatry, Pori, Finland and Medical Consultant, Viatris, Finland
| | - Christoph U Correll
- The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, New York, United States; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, New York, United States; Charité - Universitätsmedizin Berlin, Department of Child and Adolescent Psychiatry, Augustenburger Platz 1, Berlin 13353, Germany; German Center for Mental Health (DZPG), Partner Site Berlin, Berlin, Germany.
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3
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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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Das S, Samarasinghe L, Deva S, Fernandez Co EM, Poudel S, Dave T, Prasad S, Sarangi A. Complex neuropsychiatric presentation of 17q12 duplication syndrome: A case report. SAGE Open Med Case Rep 2024; 12:2050313X241233184. [PMID: 38379631 PMCID: PMC10878203 DOI: 10.1177/2050313x241233184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 01/29/2024] [Indexed: 02/22/2024] Open
Abstract
The chromosomal band 17q12 is characterized by a high density of genes and is bordered by segmental duplications, the structural arrangement of which increases the susceptibility of the region to deletions and duplications. Duplication of 17q12 is a rare genetic condition associated with variable characteristics from clinically asymptomatic to intellectual disabilities, seizures, and behavioral problems. The variability in phenotype is primarily due to variable expressivity and incomplete penetrance. Diagnosis is mostly established by chromosomal microarray. Treatment involves a multidisciplinary approach. We present a case of a 43-year-old female who initially presented with hyperphagia and was eventually diagnosed with bulimia nervosa, anxiety, mood disorder, and personality disorder. Additional research is required to better understand the impact of 17q12 duplication syndrome on the development of bulimia nervosa since its pathogenesis has not been adequately described in the current literature.
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Affiliation(s)
- Soumitra Das
- Department of Psychiatry, Western Health, Footscray, VIC, Australia
| | | | - Sheryl Deva
- Kamineni Academy of Medical Sciences and Research Center, Hyderabad, Telangana, India
| | | | | | - Tirth Dave
- Bukovinian State Medical University, Chernivtsi, Ukraine
| | - Sakshi Prasad
- Vinnytsia National Pirogov Memorial Medical University, Vinnitsya, Ukraine
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Morgenroth CL, Kleymann P, Ripke S, Awasthi S, Wagner E, Oviedo-Salcedo T, Okhuijsen-Pfeifer C, Luykx JJ, van der Horst MZ, Hasan A, Bermpohl F, Gutwinski S, Schreiter S. Polygenetic risk scores and phenotypic constellations of obsessive-compulsive disorder in clozapine-treated schizophrenia. Eur Arch Psychiatry Clin Neurosci 2024; 274:181-193. [PMID: 37020043 PMCID: PMC10786740 DOI: 10.1007/s00406-023-01593-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 03/14/2023] [Indexed: 04/07/2023]
Abstract
Obsessive-compulsive symptoms (OCS) are frequently observed in individuals with schizophrenia (SCZ) treated with clozapine (CLZ). This study aimed to analyze prevalence of OCS and obsessive-compulsive disorder (OCD) in this subgroup and find possible correlations with different phenotypes. Additionally, this is the first study to examine polygenetic risk scores (PRS) in individuals with SCZ and OCS. A multicenter cohort of 91 individuals with SCZ who were treated with CLZ was recruited and clinically and genetically assessed. Symptom severity was examined using the Positive and Negative Symptom Scale (PANSS), Clinical Global Impression Scale (CGI), the Calgary Depression Scale for Schizophrenia (CDSS), Global Assessment of Functioning Scale (GAF) and Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Participants were divided into subgroups based on phenotypic OCS or OCD using Y-BOCS scores. Genomic-wide data were generated, and PRS analyses were performed to evaluate the association between either phenotypic OCD or OCS severity and genotype-predicted predisposition for OCD, SCZ, cross-disorder, and CLZ/norclozapine (NorCLZ) ratio, CLZ metabolism and NorCLZ metabolism. OCS and OCD were frequent comorbidities in our sample of CLZ-treated SCZ individuals, with a prevalence of 39.6% and 27.5%, respectively. Furthermore, the Y-BOCS total score correlated positively with the duration of CLZ treatment in years (r = 0.28; p = 0.008) and the PANSS general psychopathology subscale score (r = 0.23; p = 0.028). A significant correlation was found between OCD occurrence and PRS for CLZ metabolism. We found no correlation between OCS severity and PRS for CLZ metabolism. We found no correlation for either OCD or OCS and PRS for OCD, cross-disorder, SCZ, CLZ/NorCLZ ratio or NorCLZ metabolism. Our study was able to replicate previous findings on clinical characteristics of CLZ-treated SCZ individuals. OCS is a frequent comorbidity in this cohort and is correlated with CLZ treatment duration in years and PANSS general psychopathology subscale score. We found a correlation between OCD and PRS for CLZ metabolism, which should be interpreted as incidental for now. Future research is necessary to replicate significant findings and to assess possible genetic predisposition of CLZ-treated individuals with SCZ to OCS/OCD. Limitations attributed to the small sample size or the inclusion of subjects on co-medication must be considered. If the association between OCD and PRS for CLZ metabolism can be replicated, it should be further evaluated if CYP1A2 alteration, respectively lower CLZ plasma level, is relevant for OCD development.
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Affiliation(s)
- Carla Lou Morgenroth
- Department of Psychiatry and Neurosciences, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany.
| | - Philipp Kleymann
- Department of Psychiatry and Neurosciences, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Stephan Ripke
- Department of Psychiatry and Neurosciences, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Swapnil Awasthi
- Department of Psychiatry and Neurosciences, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Elias Wagner
- Department of Psychiatry and Psychotherapy, University Hospital-LMU Munich, Munich, Germany
| | - Tatiana Oviedo-Salcedo
- Department of Psychiatry and Psychotherapy, University Hospital-LMU Munich, Munich, Germany
| | - Cynthia Okhuijsen-Pfeifer
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jurjen J Luykx
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Brain Center Rudolf Magnus, Department of Translational Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
- GGNet Mental Health, Warnsveld, The Netherlands
| | - Marte Z van der Horst
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- GGNet Mental Health, Warnsveld, The Netherlands
| | - Alkomiet Hasan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, University of Augsburg, Bezirkskrankenhaus Augsburg, Augsburg, Germany
| | - Felix Bermpohl
- Department of Psychiatry and Neurosciences, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Stefan Gutwinski
- Department of Psychiatry and Neurosciences, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
- Department of Psychiatry, St. Hedwig-Krankenhaus, Charité-Universitätsmedizin, Berlin, Germany
| | - Stefanie Schreiter
- Department of Psychiatry and Neurosciences, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
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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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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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8
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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: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 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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Kato H, Kimura H, Kushima I, Takahashi N, Aleksic B, Ozaki N. The genetic architecture of schizophrenia: review of large-scale genetic studies. J Hum Genet 2023; 68:175-182. [PMID: 35821406 DOI: 10.1038/s10038-022-01059-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 06/12/2022] [Accepted: 06/20/2022] [Indexed: 11/09/2022]
Abstract
Schizophrenia is a complex and often chronic psychiatric disorder with high heritability. Diagnosis of schizophrenia is still made clinically based on psychiatric symptoms; no diagnostic tests or biomarkers are available. Pathophysiology-based diagnostic scheme and treatments are also not available. Elucidation of the pathogenesis is needed for development of pathology-based diagnostics and treatments. In the past few decades, genetic research has made substantial advances in our understanding of the genetic architecture of schizophrenia. Rare copy number variations (CNVs) and rare single-nucleotide variants (SNVs) detected by whole-genome CNV analysis and whole-genome/-exome sequencing analysis have provided the great advances. Common single-nucleotide polymorphisms (SNPs) detected by large-scale genome-wide association studies have also provided important information. Large-scale genetic studies have been revealed that both rare and common genetic variants play crucial roles in this disorder. In this review, we focused on CNVs, SNVs, and SNPs, and discuss the latest research findings on the pathogenesis of schizophrenia based on these genetic variants. Rare variants with large effect sizes can provide mechanistic hypotheses. CRISPR-based genetics approaches and induced pluripotent stem cell technology can facilitate the functional analysis of these variants detected in patients with schizophrenia. Recent advances in long-read sequence technology are expected to detect variants that cannot be detected by short-read sequence technology. Various studies that bring together data from common variant and transcriptomic datasets provide biological insight. These new approaches will provide additional insight into the pathophysiology of schizophrenia and facilitate the development of pathology-based therapeutics.
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Affiliation(s)
- Hidekazu Kato
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Hiroki Kimura
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Itaru Kushima
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan.,Medical Genomics Center, Nagoya University Hospital, Nagoya, Japan
| | - Nagahide Takahashi
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Branko Aleksic
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan.
| | - Norio Ozaki
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan.,Medical Genomics Center, Nagoya University Hospital, Nagoya, Japan.,Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Japan
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10
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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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11
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Qubad M, Bittner RA. Second to none: rationale, timing, and clinical management of clozapine use in schizophrenia. Ther Adv Psychopharmacol 2023; 13:20451253231158152. [PMID: 36994117 PMCID: PMC10041648 DOI: 10.1177/20451253231158152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 01/24/2023] [Indexed: 03/31/2023] Open
Abstract
Despite its enduring relevance as the single most effective and important evidence-based treatment for schizophrenia, underutilization of clozapine remains considerable. To a substantial degree, this is attributable to a reluctance of psychiatrists to offer clozapine due to its relatively large side-effect burden and the complexity of its use. This underscores the necessity for continued education regarding both the vital nature and the intricacies of clozapine treatment. This narrative review summarizes all clinically relevant areas of evidence, which support clozapine's wide-ranging superior efficacy - for treatment-resistant schizophrenia (TRS) and beyond - and make its safe use eminently feasible. Converging evidence indicates that TRS constitutes a distinct albeit heterogeneous subgroup of schizophrenias primarily responsive to clozapine. Most importantly, the predominantly early onset of treatment resistance and the considerable decline in response rates associated with its delayed initiation make clozapine an essential treatment option throughout the course of illness, beginning with the first psychotic episode. To maximize patients' benefits, systematic early recognition efforts based on stringent use of TRS criteria, a timely offer of clozapine, thorough side-effect screening and management as well as consistent use of therapeutic drug monitoring and established augmentation strategies for suboptimal responders are crucial. To minimize permanent all-cause discontinuation, re-challenges after neutropenia or myocarditis should be considered. Owing to clozapine's unique efficacy, comorbid conditions including substance use and most somatic disorders should not dissuade but rather encourage clinicians to consider clozapine. Moreover, treatment decisions need to be informed by the late onset of clozapine's full effects, which for reduced suicidality and mortality rates may not even be readily apparent. Overall, the singular extent of its efficacy combined with the high level of patient satisfaction continues to distinguish clozapine from all other available antipsychotics.
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Affiliation(s)
- Mishal Qubad
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
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12
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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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13
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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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14
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A novel longitudinal clustering approach to psychopathology across diagnostic entities in the hospital-based PsyCourse study. Schizophr Res 2022; 244:29-38. [PMID: 35567871 DOI: 10.1016/j.schres.2022.05.001] [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: 11/16/2020] [Revised: 01/23/2022] [Accepted: 05/02/2022] [Indexed: 12/21/2022]
Abstract
Biological research and clinical management in psychiatry face two major impediments: the high degree of overlap in psychopathology between diagnoses and the inherent heterogeneity with regard to severity. Here, we aim to stratify cases into homogeneous transdiagnostic subgroups using psychometric information with the ultimate aim of identifying individuals with higher risk for severe illness. 397 participants of the PsyCourse study with schizophrenia- or bipolar-spectrum diagnoses were prospectively phenotyped over 18 months. Factor analysis of mixed data of different rating scales and subsequent longitudinal clustering were used to cluster disease trajectories. Five clusters of longitudinal trajectories were identified in the psychopathologic dimensions. Clusters differed significantly with regard to Global Assessment of Functioning, disease course, and-in some cases-diagnosis while there were no significant differences regarding sex, age at baseline or onset, duration of illness, or polygenic burden for schizophrenia. Longitudinal clustering may aid in identifying transdiagnostic homogeneous subgroups of individuals with severe psychiatric disease.
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15
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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: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [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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16
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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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17
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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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18
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Johnson D, Wilke MA, Lyle SM, Kowalec K, Jorgensen A, Wright GE, Drögemöller BI. A systematic review and analysis of the use of polygenic scores in pharmacogenomics. Clin Pharmacol Ther 2021; 111:919-930. [PMID: 34953075 DOI: 10.1002/cpt.2520] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 12/18/2021] [Indexed: 11/09/2022]
Abstract
Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.
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Affiliation(s)
- Danielle Johnson
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - MacKenzie Ap Wilke
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Sarah M Lyle
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Kaarina Kowalec
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Andrea Jorgensen
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Galen Eb Wright
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre and Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada
| | - Britt I Drögemöller
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,CancerCare Manitoba Research Institute, Winnipeg, MB, Canada.,Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
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19
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Tosato S, Bonetto C, Vassos E, Lasalvia A, De Santi K, Gelmetti M, Cristofalo D, Richards A, Ruggeri M. Obstetric Complications and Polygenic Risk Score: Which Role in Predicting a Severe Short-Term Outcome in Psychosis? Genes (Basel) 2021; 12:1895. [PMID: 34946845 PMCID: PMC8702213 DOI: 10.3390/genes12121895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 11/17/2021] [Accepted: 11/25/2021] [Indexed: 11/17/2022] Open
Abstract
Understanding and improving the outcomes of psychosis remains a major challenge for clinical research. Obstetric complications (OCs) as a risk factor for schizophrenia (SZ) have been investigated as a potential predictor of outcomes in relation to illness severity and poorer treatment outcome, but there are less reports on first episode psychosis (FEP) patients. We test whether OCs, collected in a cohort of FEP patients, can predict illness course and psychopathology severity after 2 years from the onset. Moreover, we explore whether the SZ-polygenic risk score (PRS) would predict the illness course and whether the interaction between OCS and PRS shows a significant effect. A cohort of 264 FEP patients were assessed with standardized instruments. OCs were recorded using the Lewis-Murray scale in interviews with the patients' mothers: 30% of them reported at least one OC. Patients with at least one OC were more likely to have a non-remitting course of illness compared to those without OCs (35.3% vs. 16.3%, p = 0.014). No association between SZ-PRS and course of illness nor evidence for a gene-environment interaction was found. In our sample, poor short-term outcomes were associated with OCs, while SZ-PRS was not a prognostic indicator of poor outcomes.
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Affiliation(s)
- Sarah Tosato
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (C.B.); (A.L.); (M.G.); (D.C.); (M.R.)
| | - Chiara Bonetto
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (C.B.); (A.L.); (M.G.); (D.C.); (M.R.)
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London SE5 8AF, UK;
- The National Institute for Health Research, Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, London SE5 8AF, UK
| | - Antonio Lasalvia
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (C.B.); (A.L.); (M.G.); (D.C.); (M.R.)
| | - Katia De Santi
- Unit of Psychiatry, Azienda Ospedaliera Universitaria Integrata, 37134 Verona, Italy;
| | - Margherita Gelmetti
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (C.B.); (A.L.); (M.G.); (D.C.); (M.R.)
| | - Doriana Cristofalo
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (C.B.); (A.L.); (M.G.); (D.C.); (M.R.)
| | - Alexander Richards
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff CF24 4HQ, UK;
| | - Mirella Ruggeri
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (C.B.); (A.L.); (M.G.); (D.C.); (M.R.)
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20
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Smigielski L, Papiol S, Theodoridou A, Heekeren K, Gerstenberg M, Wotruba D, Buechler R, Hoffmann P, Herms S, Adorjan K, Anderson-Schmidt H, Budde M, Comes AL, Gade K, Heilbronner M, Heilbronner U, Kalman JL, Klöhn-Saghatolislam F, Reich-Erkelenz D, Schaupp SK, Schulte EC, Senner F, Anghelescu IG, Arolt V, Baune BT, Dannlowski U, Dietrich DE, Fallgatter AJ, Figge C, Jäger M, Juckel G, Konrad C, Nieratschker V, Reimer J, Reininghaus E, Schmauß M, Spitzer C, von Hagen M, Wiltfang J, Zimmermann J, Gryaznova A, Flatau-Nagel L, Reitt M, Meyers M, Emons B, Haußleiter IS, Lang FU, Becker T, Wigand ME, Witt SH, Degenhardt F, Forstner AJ, Rietschel M, Nöthen MM, Andlauer TFM, Rössler W, Walitza S, Falkai P, Schulze TG, Grünblatt E. Polygenic risk scores across the extended psychosis spectrum. Transl Psychiatry 2021; 11:600. [PMID: 34836939 PMCID: PMC8626446 DOI: 10.1038/s41398-021-01720-0] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/24/2021] [Accepted: 10/29/2021] [Indexed: 12/23/2022] Open
Abstract
As early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke's pseudo-R2: 1.3-7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.
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Affiliation(s)
- Lukasz Smigielski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland.
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland.
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Anastasia Theodoridou
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Karsten Heekeren
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy I, LVR-Hospital, Cologne, Germany
| | - Miriam Gerstenberg
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Diana Wotruba
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Roman Buechler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland
| | - Per Hoffmann
- Department of Biomedicine, Human Genomics Research Group, University Hospital and University of Basel, Basel, Switzerland
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Stefan Herms
- Department of Biomedicine, Human Genomics Research Group, University Hospital and University of Basel, Basel, Switzerland
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Kristina Adorjan
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Heike Anderson-Schmidt
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Ashley L Comes
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Katrin Gade
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Maria Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Janos L Kalman
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | | | - Daniela Reich-Erkelenz
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Sabrina K Schaupp
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Eva C Schulte
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Fanny Senner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Ion-George Anghelescu
- Department of Psychiatry and Psychotherapy, Mental Health Institute, Berlin, Germany
| | - Volker Arolt
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Detlef E Dietrich
- AMEOS Clinical Center Hildesheim, Hildesheim, Germany
- Center for Systems Neuroscience (ZSN), Hannover, Germany
| | - Andreas J Fallgatter
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, Tübingen, Germany
| | - Christian Figge
- Karl-Jaspers Clinic, European Medical School Oldenburg-Groningen, Oldenburg, Germany
| | - Markus Jäger
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Georg Juckel
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Carsten Konrad
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg, Germany
| | - Vanessa Nieratschker
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, Tübingen, Germany
| | - Jens Reimer
- Department of Psychiatry, Klinikum Bremen-Ost, Bremen, Germany
- Department of Psychiatry, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Eva Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz, Austria
| | - Max Schmauß
- Clinic for Psychiatry, Psychotherapy and Psychosomatics, Augsburg University, Medical Faculty, Bezirkskrankenhaus Augsburg, Augsburg, Germany
| | - Carsten Spitzer
- Department of Psychosomatic Medicine and Psychotherapy, University Medical Center Rostock, Rostock, Germany
| | - Martin von Hagen
- Clinic for Psychiatry and Psychotherapy, Clinical Center Werra-Meißner, Eschwege, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Jörg Zimmermann
- Psychiatrieverbund Oldenburger Land gGmbH, Karl-Jaspers-Klinik, Bad Zwischenahn, Germany
| | - Anna Gryaznova
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Laura Flatau-Nagel
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Markus Reitt
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Milena Meyers
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Barbara Emons
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Ida Sybille Haußleiter
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Fabian U Lang
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Thomas Becker
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Moritz E Wigand
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Till F M Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Wulf Rössler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
- Laboratory of Neuroscience (LIM 27), Institute of Psychiatry, Universidade de São Paulo, São Paulo, Brazil
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Edna Grünblatt
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
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21
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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: 66] [Impact Index Per Article: 22.0] [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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22
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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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23
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Lisoway AJ, Chen CC, Zai CC, Tiwari AK, Kennedy JL. Toward personalized medicine in schizophrenia: Genetics and epigenetics of antipsychotic treatment. Schizophr Res 2021; 232:112-124. [PMID: 34049235 DOI: 10.1016/j.schres.2021.05.010] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 04/30/2021] [Accepted: 05/02/2021] [Indexed: 12/21/2022]
Abstract
Schizophrenia is a complex psychiatric disorder where genetic, epigenetic, and environmental factors play a role in disease onset, course of illness, and treatment outcome. Pharmaco(epi)genetic research presents an important opportunity to improve patient care through prediction of medication side effects and response. In this narrative review, we discuss the current state of research and important progress of both genetic and epigenetic factors involved in antipsychotic response, over the past five years. The review is largely focused on the following frequently prescribed antipsychotics: olanzapine, risperidone, aripiprazole, and clozapine. Several consistent pharmacogenetic findings have emerged, in particular pharmacokinetic genes (primarily cytochrome P450 enzymes) and pharmacodynamic genes involving dopamine, serotonin, and glutamate neurotransmission. In addition to studies analysing DNA sequence variants, there are also several pharmacoepigenetic studies of antipsychotic response that have focused on the measurement of DNA methylation. Although pharmacoepigenetics is still in its infancy, consideration of both genetic and epigenetic factors contributing to antipsychotic response and side effects no doubt will be increasingly important in personalized medicine. We provide recommendations for next steps in research and clinical evaluation.
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Affiliation(s)
- Amanda J Lisoway
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada
| | - Cheng C Chen
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada
| | - Clement C Zai
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Canada; Department of Psychiatry, University of Toronto, Canada
| | - Arun K Tiwari
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Canada
| | - James L Kennedy
- Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Canada; Department of Psychiatry, University of Toronto, Canada.
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24
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Gupta R, Bigdeli TB, Buckley PF, Fanous AH. Genetics of Schizophrenia and Bipolar Disorder: Potential Clinical Applications. Psychiatr Ann 2021. [DOI: 10.3928/00485713-20210310-01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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25
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Erzin G, Pries LK, van Os J, Fusar-Poli L, Delespaul P, Kenis G, Luykx JJ, Lin BD, Richards AL, Akdede B, Binbay T, Altınyazar V, Yalınçetin B, Gümüş-Akay G, Cihan B, Soygür H, Ulaş H, Cankurtaran EŞ, Kaymak SU, Mihaljevic MM, Andric-Petrovic S, Mirjanic T, Bernardo M, Mezquida G, Amoretti S, Bobes J, Saiz PA, García-Portilla MP, Sanjuan J, Aguilar EJ, Santos JL, Jiménez-López E, Arrojo M, Carracedo A, López G, González-Peñas J, Parellada M, Maric NP, Atbaşoğlu C, Ucok A, Alptekin K, Saka MC, Arango C, O'Donovan MC, Rutten BPF, Guloksuz S. Examining the association between exposome score for schizophrenia and functioning in schizophrenia, siblings, and healthy controls: Results from the EUGEI study. Eur Psychiatry 2021; 64:e25. [PMID: 33736735 PMCID: PMC8080213 DOI: 10.1192/j.eurpsy.2021.19] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Background A cumulative environmental exposure score for schizophrenia (exposome score for schizophrenia [ES-SCZ]) may provide potential utility for risk stratification and outcome prediction. Here, we investigated whether ES-SCZ was associated with functioning in patients with schizophrenia spectrum disorder, unaffected siblings, and healthy controls. Methods This cross-sectional sample consisted of 1,261 patients, 1,282 unaffected siblings, and 1,525 healthy controls. The Global Assessment of Functioning (GAF) scale was used to assess functioning. ES-SCZ was calculated based on our previously validated method. The association between ES-SCZ and the GAF dimensions (symptom and disability) was analyzed by applying regression models in each group (patients, siblings, and controls). Additional models included polygenic risk score for schizophrenia (PRS-SCZ) as a covariate. Results ES-SCZ was associated with the GAF dimensions in patients (symptom: B = −1.53, p-value = 0.001; disability: B = −1.44, p-value = 0.001), siblings (symptom: B = −3.07, p-value < 0.001; disability: B = −2.52, p-value < 0.001), and healthy controls (symptom: B = −1.50, p-value < 0.001; disability: B = −1.31, p-value < 0.001). The results remained the same after adjusting for PRS-SCZ. The degree of associations of ES-SCZ with both symptom and disability dimensions were higher in unaffected siblings than in patients and controls. By analyzing an independent dataset (the Genetic Risk and Outcome of Psychosis study), we replicated the results observed in the patient group. Conclusions Our findings suggest that ES-SCZ shows promise for enhancing risk prediction and stratification in research practice. From a clinical perspective, ES-SCZ may aid in efforts of clinical characterization, operationalizing transdiagnostic clinical staging models, and personalizing clinical management.
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Affiliation(s)
- Gamze Erzin
- Department of Psychiatry, University of Health Sciences Ankara Diskapi Training and Research Hospital, Ankara, Turkey.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Lotta-Katrin Pries
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands.,Department of Psychiatry, UUMC Utrecht Brain Centre, University Medical Centre Utrecht, trecht University, Utrecht, The Netherlands.,Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Laura Fusar-Poli
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Catania, Italy
| | - Philippe Delespaul
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands.,FACT, Mondriaan Mental Health, Maastricht, The Netherlands
| | - Gunter Kenis
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Jurjen J Luykx
- Department of Psychiatry, UUMC Utrecht Brain Centre, University Medical Centre Utrecht, trecht University, Utrecht, The Netherlands.,Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,GGNet Mental Health, Apeldoorn, The Netherlands
| | - Bochao D Lin
- Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Alexander L Richards
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Berna Akdede
- Department of Psychiatry, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Tolga Binbay
- Department of Psychiatry, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Vesile Altınyazar
- Department of Psychiatry, Faculty of Medicine, Adnan Menderes University, Aydin, Turkey
| | - Berna Yalınçetin
- Department of Neuroscience, Graduate School of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Güvem Gümüş-Akay
- Department of Physiology, School of Medicine, Ankara University, Ankara, Turkey.,Brain Research Center, Ankara University, Ankara, Turkey.,Neuroscience and Neurotechnology Center of Excellence (NÖROM), Ankara, Turkey
| | - Burçin Cihan
- Department of Psychology, Middle East Technical University, Ankara, Turkey
| | - Haldun Soygür
- Turkish Federation of Schizophrenia Associations, Ankara, Turkey
| | - Halis Ulaş
- Department of Psychiatry, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | | | | | - Marina M Mihaljevic
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia.,Clinic for Psychiatry Clinical Centre of Serbia, Belgrade, Serbia
| | - Sanja Andric-Petrovic
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia.,Clinic for Psychiatry Clinical Centre of Serbia, Belgrade, Serbia
| | - Tijana Mirjanic
- Special Hospital for Psychiatric Disorders Kovin, Kovin, Serbia
| | - Miguel Bernardo
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain.,Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain
| | - Gisela Mezquida
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain.,Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain
| | - Silvia Amoretti
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain.,Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain
| | - Julio Bobes
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Psychiatry, School of Medicine, University of Oviedo, Oviedo, Spain.,Instituto de Investigación Sanitaria del Principado de Asturias, Oviedo, Spain.,Mental Health Services of Principado de Asturias, Oviedo, Spain
| | - Pilar A Saiz
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Psychiatry, School of Medicine, University of Oviedo, Oviedo, Spain.,Instituto de Investigación Sanitaria del Principado de Asturias, Oviedo, Spain.,Mental Health Services of Principado de Asturias, Oviedo, Spain
| | - Maria Paz García-Portilla
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Psychiatry, School of Medicine, University of Oviedo, Oviedo, Spain.,Instituto de Investigación Sanitaria del Principado de Asturias, Oviedo, Spain.,Mental Health Services of Principado de Asturias, Oviedo, Spain
| | - Julio Sanjuan
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Psychiatry, Hospital Clínico Universitario de Valencia, INCLIVA, School of Medicine, Universidad de Valencia, Valencia, Spain
| | - Eduardo J Aguilar
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Psychiatry, Hospital Clínico Universitario de Valencia, INCLIVA, School of Medicine, Universidad de Valencia, Valencia, Spain
| | - Jose Luis Santos
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Psychiatry, Hospital Virgen de la Luz, Cuenca, Spain
| | - Estela Jiménez-López
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Health and Social Research Center, Universidad de Castilla-La Mancha, Cuenca, Spain
| | - Manuel Arrojo
- Department of Psychiatry, Instituto de Investigación Sanitaria, Complejo Hospitalario Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Angel Carracedo
- Grupo de Medicina Genómica, Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Universidad de Santiago de Compostela, Santiago de Compostela, Spain.,Fundación Pública Galega de Medicina Xenómica (SERGAS), Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Gonzalo López
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, Madrid, Spain
| | - Javier González-Peñas
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, Madrid, Spain
| | - Mara Parellada
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nadja P Maric
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia.,Institute of Mental Health, Belgrade, Serbia
| | - Cem Atbaşoğlu
- Department of Psychiatry, School of Medicine, Ankara University, Ankara, Turkey
| | - Alp Ucok
- Department of Psychiatry, Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Köksal Alptekin
- Department of Psychiatry, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey.,Department of Neuroscience, Graduate School of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Meram Can Saka
- Department of Psychiatry, School of Medicine, Ankara University, Ankara, Turkey
| | | | - Celso Arango
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.,Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, Madrid, Spain
| | - Micheal C O'Donovan
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands.,Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
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26
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Penders B, Janssens ACJW. Do we measure or compute polygenic risk scores? Why language matters. Hum Genet 2021; 141:1093-1097. [PMID: 33587168 DOI: 10.1007/s00439-021-02262-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 02/02/2021] [Indexed: 09/03/2023]
Abstract
Here, we argue that polygenic risk scores (PRSs) are different epistemic objects as compared to other biomarkers such as blood pressure or sodium level. While the latter two may be subject to variation, measured inaccurately or interpreted in various ways, blood flow has pressure and sodium is available in a concentration that can be quantified and visualised. In stark contrast, PRSs are calculated, compiled or constructed through the statistical assemblage of genetic variants. How researchers frame and name PRSs has consequences for how we interpret and value their results. We distinguish between the tangible and inferential understanding of PRS and the corresponding languages of measurement and computation, respectively. The conflation of these frames obscures important questions we need to ask: what PRS seeks to represent, whether current ways of 'doing PRS' are optimal and responsible, and upon what we base the credibility of PRS-based knowledge claims.
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Affiliation(s)
- Bart Penders
- Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands
| | - A Cecile J W Janssens
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia.
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27
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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: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 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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28
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Qin Y, Kang J, Jiao Z, Wang Y, Wang J, Wang H, Feng J, Jin L, Wang F, Gong X. Polygenic risk for autism spectrum disorder affects left amygdala activity and negative emotion in schizophrenia. Transl Psychiatry 2020; 10:322. [PMID: 32958750 PMCID: PMC7506524 DOI: 10.1038/s41398-020-01001-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 09/02/2020] [Accepted: 09/07/2020] [Indexed: 12/27/2022] Open
Abstract
Although the diagnoses based on phenomenology have many practical advantages, accumulating evidence shows that schizophrenia and autism spectrum disorder (ASD) share some overlap in genetics and clinical presentation. It remains largely unknown how ASD-associated polygenetic risk contributes to the pathogenesis of schizophrenia. In the present study, we calculated high-resolution ASD polygenic risk scores (ASD PRSs) and selected optimal ten ASD PRS with minimal P values in the association analysis of PRSs, with schizophrenia to assess the effect of ASD PRS on brain neural activity in schizophrenia cases and controls. We found that amplitude of low-frequency fluctuation in left amygdala was positively associated with ASD PRSs in our cohort. Correlation analysis of ASD PRSs with facial emotion recognition test identified the negative correlation of ASD PRSs with negative emotions in schizophrenia cases and controls. Finally, functional enrichment analysis of PRS genes revealed that neural system function and development, as well as signal transduction, were mainly enriched in PRS genes. Our results provide empirical evidence that polygenic risk for ASD contributes to schizophrenia by the intermediate phenotypes of left amygdala function and emotion recognition. It provides a promising strategy to understand the relationship between phenotypes and genotypes shared in mental disorders.
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Affiliation(s)
- Yue Qin
- grid.8547.e0000 0001 0125 2443State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Jujiao Kang
- grid.8547.e0000 0001 0125 2443Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Zeyu Jiao
- grid.8547.e0000 0001 0125 2443Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Yi Wang
- grid.8547.e0000 0001 0125 2443State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Jiucun Wang
- grid.8547.e0000 0001 0125 2443State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443Human Phoneme Institute, Fudan University, Shanghai, China
| | - Hongyan Wang
- grid.8547.e0000 0001 0125 2443State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
| | - Jianfeng Feng
- grid.8547.e0000 0001 0125 2443Shanghai Center for Mathematical Science, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China ,grid.7372.10000 0000 8809 1613Department of Computer Science, University of Warwick, Coventry, CV4 7AL UK
| | - Li Jin
- grid.8547.e0000 0001 0125 2443State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Fei Wang
- grid.412636.4Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xiaohong Gong
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China.
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29
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Prospects of Genetics and Epigenetics of Alcohol Use Disorder. CURRENT ADDICTION REPORTS 2020. [DOI: 10.1007/s40429-020-00331-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Abstract
Purpose of Review
In this study, we illustrate recent findings regarding the genetics and epigenetics of alcohol use disorder (AUD). We further outline the future direction of genetic and epigenetic research in AUD.
Recent Findings
Recent genome- and epigenome-wide studies allow new insight into genetic and epigenetic variation associated with AUD. The largest EWAS of AUD so far/to date found evidence for altered glucocorticoid receptor regulation. Longitudinal studies provide insight into the dynamics of the disease. Analyses of postmortem brain tissue reveal the impact of chronic alcohol consumption on DNA methylation in the brain.
Summary
Genetic and environmental factors—mediated via epigenetic mechanisms—play an important role in AUD. Although knowledge of the biological underpinnings of AUD is still limited, ongoing research will ultimately lead to the development of biomarkers for disease classification, course of disease, and treatment response to support personalized medicine in the future.
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Meiser B, Guo XY, Putt S, Fullerton JM, Schofield PR, Mitchell PB, Yanes T. Psychosocial implications of living with familial risk of a psychiatric disorder and attitudes to psychiatric genetic testing: A systematic review of the literature. Am J Med Genet B Neuropsychiatr Genet 2020; 183:277-288. [PMID: 32369270 DOI: 10.1002/ajmg.b.32786] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 02/25/2020] [Accepted: 03/09/2020] [Indexed: 01/12/2023]
Abstract
The aim of this systematic review was to synthesize the existing evidence documenting the psychosocial implications of living with a familial risk of an adult-onset psychiatric disorder. Six databases were searched systematically to identify qualitative and quantitative studies, which explored perspectives of those at increased risk for psychiatric disorders, as well as the general public. Thematic analysis was used to identify major themes. Thirty-five articles met the eligibility criteria and reported on the views of 4,896 participants. The literature demonstrates strong interest in psychiatric genetic testing of adults as well as children, whereas attitudes toward prenatal testing were much less positive. Predictors of interest in testing, as well as perceived advantages and disadvantages were identified. Very few studies are available on anticipated and actual reactions to receiving results. Studies show that the majority of participants feel that having a genetic explanation would alleviate some of the stigma associated with mental illness. This review shows that interest in, and predictors of attitudes toward, psychiatric genetic testing are well researched, but the extent to which attitudes will translate into actual testing uptake is unknown. Future research also needs to assess the actual behavioral and psychological impact of genetic testing.
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Affiliation(s)
- Bettina Meiser
- Psychosocial Research Group, Prince of Wales Clinical School, University of New South Wales Sydney, Sydney, Australia
| | - Xin Y Guo
- Psychosocial Research Group, Prince of Wales Clinical School, University of New South Wales Sydney, Sydney, Australia
| | - Sophie Putt
- Psychosocial Research Group, Prince of Wales Clinical School, University of New South Wales Sydney, Sydney, Australia
| | - Janice M Fullerton
- Neuroscience Research Australia, Sydney, Australia.,School of Medical Sciences, UNSW, Sydney, Australia
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, Australia.,School of Medical Sciences, UNSW, Sydney, Australia
| | - Philip B Mitchell
- School of Psychiatry, University of New South Wales, Sydney, Australia.,Black Dog Institute, Prince of Wales Hospital, Sydney, Australia
| | - Tatiane Yanes
- Psychosocial Research Group, Prince of Wales Clinical School, University of New South Wales Sydney, Sydney, Australia
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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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Dwyer DB, Kalman JL, Budde M, Kambeitz J, Ruef A, Antonucci LA, Kambeitz-Ilankovic L, Hasan A, Kondofersky I, Anderson-Schmidt H, Gade K, Reich-Erkelenz D, Adorjan K, Senner F, Schaupp S, Andlauer TFM, Comes AL, Schulte EC, Klöhn-Saghatolislam F, Gryaznova A, Hake M, Bartholdi K, Flatau-Nagel L, Reitt M, Quast S, Stegmaier S, Meyers M, Emons B, Haußleiter IS, Juckel G, Nieratschker V, Dannlowski U, Yoshida T, Schmauß M, Zimmermann J, Reimer J, Wiltfang J, Reininghaus E, Anghelescu IG, Arolt V, Baune BT, Konrad C, Thiel A, Fallgatter AJ, Figge C, von Hagen M, Koller M, Lang FU, Wigand ME, Becker T, Jäger M, Dietrich DE, Scherk H, Spitzer C, Folkerts H, Witt SH, Degenhardt F, Forstner AJ, Rietschel M, Nöthen MM, Mueller N, Papiol S, Heilbronner U, Falkai P, Schulze TG, Koutsouleris N. An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings: The PsyCourse Study. JAMA Psychiatry 2020; 77:523-533. [PMID: 32049274 PMCID: PMC7042925 DOI: 10.1001/jamapsychiatry.2019.4910] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
IMPORTANCE Identifying psychosis subgroups could improve clinical and research precision. Research has focused on symptom subgroups, but there is a need to consider a broader clinical spectrum, disentangle illness trajectories, and investigate genetic associations. OBJECTIVE To detect psychosis subgroups using data-driven methods and examine their illness courses over 1.5 years and polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational achievement. DESIGN, SETTING, AND PARTICIPANTS This ongoing multisite, naturalistic, longitudinal (6-month intervals) cohort study began in January 2012 across 18 sites. Data from a referred sample of 1223 individuals (765 in the discovery sample and 458 in the validation sample) with DSM-IV diagnoses of schizophrenia, bipolar affective disorder (I/II), schizoaffective disorder, schizophreniform disorder, and brief psychotic disorder were collected from secondary and tertiary care sites. Discovery data were extracted in September 2016 and analyzed from November 2016 to January 2018, and prospective validation data were extracted in October 2018 and analyzed from January to May 2019. MAIN OUTCOMES AND MEASURES A clinical battery of 188 variables measuring demographic characteristics, clinical history, symptoms, functioning, and cognition was decomposed using nonnegative matrix factorization clustering. Subtype-specific illness courses were compared with mixed models and polygenic scores with analysis of covariance. Supervised learning was used to replicate results in validation data with the most reliably discriminative 45 variables. RESULTS Of the 765 individuals in the discovery sample, 341 (44.6%) were women, and the mean (SD) age was 42.7 (12.9) years. Five subgroups were found and labeled as affective psychosis (n = 252), suicidal psychosis (n = 44), depressive psychosis (n = 131), high-functioning psychosis (n = 252), and severe psychosis (n = 86). Illness courses with significant quadratic interaction terms were found for psychosis symptoms (R2 = 0.41; 95% CI, 0.38-0.44), depression symptoms (R2 = 0.28; 95% CI, 0.25-0.32), global functioning (R2 = 0.16; 95% CI, 0.14-0.20), and quality of life (R2 = 0.20; 95% CI, 0.17-0.23). The depressive and severe psychosis subgroups exhibited the lowest functioning and quadratic illness courses with partial recovery followed by reoccurrence of severe illness. Differences were found for educational attainment polygenic scores (mean [SD] partial η2 = 0.014 [0.003]) but not for diagnostic polygenic risk. Results were largely replicated in the validation cohort. CONCLUSIONS AND RELEVANCE Psychosis subgroups were detected with distinctive clinical signatures and illness courses and specificity for a nondiagnostic genetic marker. New data-driven clinical approaches are important for future psychosis taxonomies. The findings suggest a need to consider short-term to medium-term service provision to restore functioning in patients stratified into the depressive and severe psychosis subgroups.
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Affiliation(s)
- Dominic B. Dwyer
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Janos L. Kalman
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,International Max Planck Research School (IMPRS-TP), Munich, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Joseph Kambeitz
- Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Anne Ruef
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Linda A. Antonucci
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Department of Education, Psychology and Communication, University of Bari Aldo Moro, Bari, Italy
| | | | - Alkomiet Hasan
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Ivan Kondofersky
- Institute of Computational Biology, Helmholtz Zentrum Munich, Oberschleißheim, Germany,Department of Mathematics, Technical University of Munich Garching, Garching, Germany
| | - Heike Anderson-Schmidt
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Department of Psychiatry and Psychotherapy, University Medical Center Gottingen, Gottingen, Germany
| | - Katrin Gade
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Department of Psychiatry and Psychotherapy, University Medical Center Gottingen, Gottingen, Germany
| | - Daniela Reich-Erkelenz
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Kristina Adorjan
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Fanny Senner
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Sabrina Schaupp
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Department of Psychiatry and Psychotherapy, Bezirkskrankenhaus Augsburg, Augsburg, Germany
| | - Till F. M. Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Ashley L. Comes
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,International Max Planck Research School (IMPRS-TP), Munich, Germany
| | - Eva C. Schulte
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Farah Klöhn-Saghatolislam
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Anna Gryaznova
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Maria Hake
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Kim Bartholdi
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Laura Flatau-Nagel
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Markus Reitt
- Department of Psychiatry and Psychotherapy, University Medical Center Gottingen, Gottingen, Germany
| | - Silke Quast
- Department of Psychiatry and Psychotherapy, University Medical Center Gottingen, Gottingen, Germany
| | - Sophia Stegmaier
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Milena Meyers
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Barbara Emons
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Ida Sybille Haußleiter
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Georg Juckel
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Vanessa Nieratschker
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Udo Dannlowski
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - Tomoya Yoshida
- Department of Physiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Max Schmauß
- Department of Psychiatry and Psychotherapy, Bezirkskrankenhaus Augsburg, Augsburg, Germany
| | - Jörg Zimmermann
- Psychiatrieverbund Oldenburger Land gGmbH, Karl-Jaspers-Klinik, Bad Zwischenahn, Germany
| | - Jens Reimer
- Department of Psychiatry, Klinikum Bremen-Ost, Bremen, Germany,Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Gottingen, Gottingen, Germany,German Center for Neurodegenerative Diseases (DZNE), Gottingen, Germany,Institute of BioMedicine (iBiMED), Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Eva Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz, Austria
| | | | - Volker Arolt
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - Bernhard T. Baune
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany,Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia,The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Carsten Konrad
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg, Germany
| | - Andreas Thiel
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg, Germany
| | - Andreas J. Fallgatter
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Christian Figge
- Karl-Jaspers Clinic, European Medical School Oldenburg-Groningen, Oldenburg, Germany
| | - Martin von Hagen
- Clinic for Psychiatry and Psychotherapy, Clinical Center Werra-Meißner, Eschwege, Germany
| | | | - Fabian U. Lang
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Moritz E. Wigand
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Thomas Becker
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Markus Jäger
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Detlef E. Dietrich
- AMEOS Clinical Center Hildesheim, Hildesheim, Germany,Center for Systems Neuroscience, Hannover, Germany,Burghof-Klinik Rinteln, Rinteln, Germany
| | | | - Carsten Spitzer
- Department of Psychosomatics and Psychotherapeutic Medicine, University Medical Center Rostock, Rostock, Germany
| | - Here Folkerts
- Department of Psychiatry, Psychotherapy and Psychosomatics, Clinical Center Wilhelmshaven, Wilhelmshaven, Germany
| | - Stephanie H. Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, University Hospital Bonn, Bonn, Germany,Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
| | - Andreas J. Forstner
- Institute of Human Genetics, University Hospital Bonn, Bonn, Germany,Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany,Human Genomics Research Group, Department of Biomedicine, University of Basel, Basel, Switzerland,Centre for Human Genetics, University of Marburg, Marburg, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Markus M. Nöthen
- Institute of Human Genetics, University Hospital Bonn, Bonn, Germany,Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
| | - Nikola Mueller
- Institute of Computational Biology, Helmholtz Zentrum Munich, Oberschleißheim, Germany
| | - Sergi Papiol
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Thomas G. Schulze
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany,International Max-Planck Research School for Translational Psychiatry, Max-Planck Institute of Psychiatry, Munich, Germany
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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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Li A, Zalesky A, Yue W, Howes O, Yan H, Liu Y, Fan L, Whitaker KJ, Xu K, Rao G, Li J, Liu S, Wang M, Sun Y, Song M, Li P, Chen J, Chen Y, Wang H, Liu W, Li Z, Yang Y, Guo H, Wan P, Lv L, Lu L, Yan J, Song Y, Wang H, Zhang H, Wu H, Ning Y, Du Y, Cheng Y, Xu J, Xu X, Zhang D, Wang X, Jiang T, Liu B. A neuroimaging biomarker for striatal dysfunction in schizophrenia. Nat Med 2020; 26:558-565. [DOI: 10.1038/s41591-020-0793-8] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2018] [Accepted: 02/10/2020] [Indexed: 12/11/2022]
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Kogelman LJA, Esserlind AL, Francke Christensen A, Awasthi S, Ripke S, Ingason A, Davidsson OB, Erikstrup C, Hjalgrim H, Ullum H, Olesen J, Folkmann Hansen T. Migraine polygenic risk score associates with efficacy of migraine-specific drugs. NEUROLOGY-GENETICS 2019; 5:e364. [PMID: 31872049 PMCID: PMC6878840 DOI: 10.1212/nxg.0000000000000364] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Accepted: 09/04/2019] [Indexed: 01/04/2023]
Abstract
Objective To assess whether the polygenic risk score (PRS) for migraine is associated with acute and/or prophylactic migraine treatment response. Methods We interviewed 2,219 unrelated patients at the Danish Headache Center using a semistructured interview to diagnose migraine and assess acute and prophylactic drug response. All patients were genotyped. A PRS was calculated with the linkage disequilibrium pred algorithm using summary statistics from the most recent migraine genome-wide association study comprising ∼375,000 cases and controls. The PRS was scaled to a unit corresponding to a twofold increase in migraine risk, using 929 unrelated Danish controls as reference. The association of the PRS with treatment response was assessed by logistic regression, and the predictive power of the model by area under the curve using a case-control design with treatment response as outcome. Results A twofold increase in migraine risk associates with positive response to migraine-specific acute treatment (odds ratio [OR] = 1.25 [95% confidence interval (CI) = 1.05–1.49]). The association between migraine risk and migraine-specific acute treatment was replicated in an independent cohort consisting of 5,616 triptan users with prescription history (OR = 3.20 [95% CI = 1.26–8.14]). No association was found for acute treatment with non–migraine-specific weak analgesics and prophylactic treatment response. Conclusions The migraine PRS can significantly identify subgroups of patients with a higher-than-average likelihood of a positive response to triptans, which provides a first step toward genetics-based precision medicine in migraine.
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Affiliation(s)
- Lisette J A Kogelman
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Ann-Louise Esserlind
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Anne Francke Christensen
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Swapnil Awasthi
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Stephan Ripke
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Andres Ingason
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Olafur B Davidsson
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Christian Erikstrup
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Henrik Hjalgrim
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Henrik Ullum
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Jes Olesen
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
| | - Thomas Folkmann Hansen
- Danish Headache Center (L.J.A.K., A.-L.E., A.F.C., O.B.D., J.O., T.F.H.), Department of Neurology, Rigshospitalet Glostrup, Denmark; Department of Psychiatry and Psychotherapy (S.A., S.R.), Charité-Universitätsmedizin, Berlin, Germany; Analytic and Translational Genetics Unit (S.R.), Massachusetts General Hospital, Boston; Stanley Center for Psychiatric Research (S.R.), Broad Institute of MIT and Harvard, Cambridge, MA; Mental Health Centre Sct Hans (A.I.), Institute of Biological Psychiatry, Roskilde; Department of Clinical Immunology (C.E.), Aarhus University Hospital; Department of Epidemiology Research (H.H.), Statens Serum Institut, Copenhagen; and Department of Clinical Immunology (H.U.), the Blood Bank, Rigshospitalet, Copenhagen University Hospital, Denmark
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Leung CCY, Gadelrab R, Ntephe CU, McGuire PK, Demjaha A. Clinical Course, Neurobiology and Therapeutic Approaches to Treatment Resistant Schizophrenia. Toward an Integrated View. Front Psychiatry 2019; 10:601. [PMID: 31551822 PMCID: PMC6735262 DOI: 10.3389/fpsyt.2019.00601] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 07/29/2019] [Indexed: 12/19/2022] Open
Abstract
Despite considerable psychotherapeutic advancement since the discovery of chlorpromazine, almost one third of patients with schizophrenia remain resistant to dopamine-blocking antipsychotics, and continue to be exposed to unwanted and often disabling side effects, but little if any clinical benefit. Even clozapine, the superior antipsychotic treatment, is ineffective in approximately half of these patients. Thus treatment resistant schizophrenia (TRS), continues to present a major therapeutic challenge to psychiatry. The main impediment to finding novel treatments is the lack of understanding of precise molecular mechanisms leading to TRS. Not only has the neurobiology been enigmatic for decades, but accurate and early detection of patients who are at risk of not responding to dopaminergic blockade remains elusive. Fortunately, recent work has started to unravel some of the neurobiological mechanisms underlying treatment resistance, providing long awaited answers, at least to some extent. Here we focus on the scientific advances in the field, from the clinical course of TRS to neurobiology and available treatment options. We specifically emphasize emerging evidence from TRS imaging and genetic literature that implicates dysregulation in several neurotransmitters, particularly dopamine and glutamate, and in addition genetic and neural alterations that concertedly may lead to the formation of TRS. Finally, we integrate available findings into a putative model of TRS, which may provide a platform for future studies in a bid to open the avenues for subsequent development of effective therapeutics.
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Affiliation(s)
- Cheryl Cheuk-Yan Leung
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience (IoPPN), King’s College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Romayne Gadelrab
- South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | | | - Philip K. McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience (IoPPN), King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Biomedical Research Centre (BRC), South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Arsime Demjaha
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience (IoPPN), King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Biomedical Research Centre (BRC), South London and Maudsley NHS Foundation Trust, London, United Kingdom
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Lin AS, Chan HY, Peng YC, Chen WJ. Severity in sustained attention impairment and clozapine-resistant schizophrenia: a retrospective study. BMC Psychiatry 2019; 19:220. [PMID: 31299940 PMCID: PMC6626410 DOI: 10.1186/s12888-019-2204-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 07/04/2019] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Among patients with treatment-resistant schizophrenia (TRS), some exhibited further clozapine resistance (CR). This study aimed to investigate whether greater severity of treatment resistance in schizophrenia is associated with greater impairments in sustained attention. METHODS Patients with a DSM-IV-defined schizophrenia were recruited from a psychiatric center in northern Taiwan (April 2010 to October 2010). Both TRS and CR were determined retrospectively from participants' medical records following the consensus guidelines. The patients were divided into three groups: 102 non-TRS, 48 TRS without CR, and 54 TRS with CR. They underwent both undegraded and degraded Continuous Performance Tests (CPT), and their performance scores (d') were standardized against a community sample to derive age-, sex-, and education-adjusted z scores. RESULTS The TRS with CR group had significantly lower adjusted z scores of d' on both undegraded and degraded CPTs than the other two groups. Meanwhile, the differences between the TRS without CR group and the non-TRS group were not significant. Multivariable linear regression analyses with adjustment for covariates revealed a trend of gradient impairments on the degraded CPT from non-TRS to TRS without CR and to TRS with CR. The proportions of attentional deficits (an adjusted z score of ≤ - 2.5) on the degraded CPT also exhibited a significant trend, from 36.3% in the non-TRS group to 62.5% in the TRS without CR group and to 83.3% in the TRS with CR group. CONCLUSIONS Greater severity of treatment resistance in schizophrenia was associated with greater impairments in sustained attention, indicating some common vulnerability.
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Affiliation(s)
- An-Sheng Lin
- grid.454740.6Department of General Psychiatry, Taoyuan Psychiatric Center, Ministry of Health and Welfare, Taoyuan, Taiwan
| | - Hung-Yu Chan
- grid.454740.6Office of Superintendent, Taoyuan Psychiatric Center, Ministry of Health and Welfare, Taoyuan, Taiwan ,0000 0004 0546 0241grid.19188.39Department of Psychiatry, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ying-Chieh Peng
- grid.454740.6Department of General Psychiatry, Bali Psychiatric Center, Ministry of Health and Welfare, New Taipei City, Taiwan
| | - Wei J. Chen
- 0000 0004 0546 0241grid.19188.39Department of Psychiatry, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan ,0000 0004 0546 0241grid.19188.39Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, 17 Xu-Zhou Road, Taipei, 100 Taiwan
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Molent C, Olivo D, Wolf RC, Balestrieri M, Sambataro F. Functional neuroimaging in treatment resistant schizophrenia: A systematic review. Neurosci Biobehav Rev 2019; 104:178-190. [PMID: 31276716 DOI: 10.1016/j.neubiorev.2019.07.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 06/25/2019] [Accepted: 07/01/2019] [Indexed: 01/06/2023]
Abstract
Despite the availability of several drugs, about 30% of patients with schizophrenia still fail to respond properly to a course of appropriate antipsychotic treatment. Functional neuroimaging studies have shown widespread patterns of altered activation and functional connectivity in treatment-resistant schizophrenia (TRS). The aim of the present study was to examine the available functional magnetic resonance imaging studies investigating TRS and to identify common patterns of altered brain function that could predict the lack of response to antipsychotic treatment in this disorder. Alterations of activation and functional connectivity in fronto-temporal, cortico-striatal, default mode network and salience networks, and of their interplay, were associated with TRS. Our findings support the notion that large-scale network alterations present in schizophrenia lie in a continuum within treatment response with the most severe dysfunction in TRS. Few studies with small sample size and without adequate control group limit the generalizability of current literature. Future controlled longitudinal studies are needed to identify neuroimaging biomarkers of pharmacotherapy response to inform individual treatment selection and facilitate early clinical response.
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Affiliation(s)
- Cinzia Molent
- Department of Medicine (DAME), University of Udine, Udine, Italy
| | - Daniele Olivo
- Department of Medicine (DAME), University of Udine, Udine, Italy; Department of Neuroscience (DNS), University of Padova, Padua, Italy
| | - Robert Christian Wolf
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Germany
| | | | - Fabio Sambataro
- Department of Medicine (DAME), University of Udine, Udine, Italy; Department of Neuroscience (DNS), University of Padova, Padua, Italy.
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Vita A, Minelli A, Barlati S, Deste G, Giacopuzzi E, Valsecchi P, Turrina C, Gennarelli M. Treatment-Resistant Schizophrenia: Genetic and Neuroimaging Correlates. Front Pharmacol 2019; 10:402. [PMID: 31040787 PMCID: PMC6476957 DOI: 10.3389/fphar.2019.00402] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Accepted: 04/01/2019] [Indexed: 12/11/2022] Open
Abstract
Schizophrenia is a severe neuropsychiatric disorder that affects approximately 0.5–1% of the population. Response to antipsychotic therapy is highly variable, and it is not currently possible to predict those patients who will or will not respond to antipsychotic medication. Furthermore, a high percentage of patients, approximately 30%, are classified as treatment-resistant (treatment-resistant schizophrenia; TRS). TRS is defined as a non-response to at least two trials of antipsychotic medication of adequate dose and duration. These patients are usually treated with clozapine, the only evidence-based pharmacotherapy for TRS. However, clozapine is associated with severe adverse events. For these reasons, there is an increasing interest to identify better targets for drug development of new compounds and to establish better biomarkers for existing medications. The ability of antipsychotics to improve psychotic symptoms is dependent on their antagonist and reverse agonist activities at different neuroreceptors, and some genetic association studies of TRS have focused on different pharmacodynamic factors. Some genetic studies have shown an association between antipsychotic response or TRS and neurodevelopment candidate genes, antipsychotic mechanisms of action (such as dopaminergic, serotonergic, GABAergic, and glutamatergic) or pharmacokinetic factors (i.e., differences in the cytochrome families). Moreover, there is a growing body of literature on the structural and functional neuroimaging research into TRS. Neuroimaging studies can help to uncover the underlying neurobiological reasons for such resistance and identify resistant patients earlier. Studies examining the neuropharmacological mechanisms of antipsychotics, including clozapine, can help to improve our knowledge of their action on the central nervous system, with further implications for the discovery of biomarkers and the development of new treatments. The identification of the underlying mechanisms of TRS is a major challenge for developing personalized medicine in the psychiatric field for schizophrenia treatment. The main goal of precision medicine is to use genetic and brain-imaging information to improve the safety, effectiveness, and health outcomes of patients via more efficiently targeted risk stratification, prevention, and tailored medication and treatment management approaches. The aim of this review is to summarize the state of art of pharmacogenetic, pharmacogenomic and neuroimaging studies in TRS.
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Affiliation(s)
- Antonio Vita
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Alessandra Minelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Stefano Barlati
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Giacomo Deste
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy
| | - Edoardo Giacopuzzi
- Genetic Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Paolo Valsecchi
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Cesare Turrina
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.,Genetic Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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Palk AC, Dalvie S, de Vries J, Martin AR, Stein DJ. Potential use of clinical polygenic risk scores in psychiatry - ethical implications and communicating high polygenic risk. Philos Ethics Humanit Med 2019; 14:4. [PMID: 30813945 PMCID: PMC6391805 DOI: 10.1186/s13010-019-0073-8] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 02/14/2019] [Indexed: 06/09/2023] Open
Abstract
Psychiatric disorders present distinct clinical challenges which are partly attributable to their multifactorial aetiology and the absence of laboratory tests that can be used to confirm diagnosis or predict risk. Psychiatric disorders are highly heritable, but also polygenic, with genetic risk conferred by interactions between thousands of variants of small effect that can be summarized in a polygenic risk score. We discuss four areas in which the use of polygenic risk scores in psychiatric research and clinical contexts could have ethical implications. First, there is concern that clinical use of polygenic risk scores may exacerbate existing health inequities. Second, research findings regarding polygenic risk could be misinterpreted in stigmatising or discriminatory ways. Third, there are concerns associated with testing minors as well as eugenics concerns elicited by prenatal polygenic risk testing. Fourth, potential challenges that could arise with the feedback and interpretation of high polygenic risk for a psychiatric disorder would require consideration. While there would be extensive overlap with the challenges of feeding back genetic findings in general, the potential clinical use of polygenic risk scoring warrants discussion in its own right, given the recency of this possibility. To this end, we discuss how lay interpretations of risk and genetic information could intersect. Consideration of these factors would be necessary for ensuring effective and constructive communication and interpretation of polygenic risk information which, in turn, could have implications for the uptake of any therapeutic recommendations. Recent advances in polygenic risk scoring have major implications for its clinical potential, however, care should be taken to ensure that communication of polygenic risk does not feed into problematic assumptions regarding mental disorders or support reductive interpretations.
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Affiliation(s)
- A. C. Palk
- Department of Psychiatry, University of Cape Town, Groote Schuur Hospital, Observatory, Cape Town, 7925 South Africa
| | - S. Dalvie
- Department of Psychiatry and SA MRC Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Groote Schuur Hospital, Observatory, Cape Town, 7925 South Africa
| | - J. de Vries
- Department of Medicine, University of Cape Town, Groote Schuur Hospital, Observatory, Cape Town, 7925 South Africa
| | - A. R. Martin
- Analytic & Translational Genetics Unit, Massachusetts General Hospital, Boston, MA USA
- Stanley Center for Psychiatric Research & Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - D. J. Stein
- Department of Psychiatry and SA MRC Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Groote Schuur Hospital, Observatory, Cape Town, 7925 South Africa
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Nöthen MM, Degenhardt F, Forstner AJ. [Breakthrough in understanding the molecular causes of psychiatric disorders]. DER NERVENARZT 2019; 90:99-106. [PMID: 30758637 DOI: 10.1007/s00115-018-0670-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
A long-established hypothesis is that genetic factors contribute to the development of psychiatric diseases, including common illnesses such as schizophrenia and the affective disorders; however, reliable molecular identification of these factors represents a far more recent innovation. This has been rendered possible by technological advances in the individual characterization of the human genome and the combining of large genetic datasets at the international level. For the first time, the results of genome-wide analyses provide researchers with systematic insights into disease-relevant biological mechanisms. Here, the integrated analysis of different omics level data generates important insights into the functional interpretation of the genetic findings. The results of genetic studies also demonstrated the degree of etiological overlap between differing psychiatric disorders, with the greatest commonality having been observed to date between schizophrenia and bipolar affective disorder. Although the translation of genetic findings into routine clinical practice is being pursued at various levels, elaborate follow-up studies are typically necessary. The diagnostic investigation of rare genomic deletions/duplications (so-called copy number variants) in patients with schizophrenia is likely to represent one of the first examples of routine clinical application. The necessary prerequisites for this are currently being defined.
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Affiliation(s)
- Markus M Nöthen
- Institut für Humangenetik, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland.
| | - Franziska Degenhardt
- Institut für Humangenetik, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland
| | - Andreas J Forstner
- Institut für Humangenetik, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland.,Zentrum für Humangenetik, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Deutschland
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Zhang JP, Robinson D, Yu J, Gallego J, Wolfgang Fleischhacker W, Kahn RS, Crespo-Facorro B, Vazquez-Bourgon J, Kane JM, Malhotra AK, Lencz T. Schizophrenia Polygenic Risk Score as a Predictor of Antipsychotic Efficacy in First-Episode Psychosis. Am J Psychiatry 2019; 176:21-28. [PMID: 30392411 PMCID: PMC6461047 DOI: 10.1176/appi.ajp.2018.17121363] [Citation(s) in RCA: 102] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Pharmacogenomic studies of antipsychotics have typically examined effects of individual polymorphisms. By contrast, polygenic risk scores (PRSs) derived from genome-wide association studies (GWAS) can quantify the influence of thousands of common alleles of small effect in a single measure. The authors examined whether PRSs for schizophrenia were predictive of antipsychotic efficacy in four independent cohorts of patients with first-episode psychosis (total N=510). METHOD All study subjects received initial treatment with antipsychotic medication for first-episode psychosis, and all were genotyped on standard single-nucleotide polymorphism (SNP) arrays imputed to the 1000 Genomes Project reference panel. PRS was computed based on the results of the large-scale schizophrenia GWAS reported by the Psychiatric Genomics Consortium. Symptoms were measured by using total symptom rating scales at baseline and at week 12 or at the last follow-up visit before dropout. RESULTS In the discovery cohort, higher PRS significantly predicted higher symptom scores at the 12-week follow-up (controlling for baseline symptoms, sex, age, and ethnicity). The PRS threshold set at a p value <0.01 gave the strongest result in the discovery cohort and was used to replicate the findings in the other three cohorts. Higher PRS significantly predicted greater posttreatment symptoms in the combined replication analysis and was individually significant in two of the three replication cohorts. Across the four cohorts, PRS was significantly predictive of adjusted 12-week symptom scores (pooled partial r=0.18; 3.24% of variance explained). Patients with low PRS were more likely to be treatment responders than patients with high PRS (odds ratio=1.91 in the two Caucasian samples). CONCLUSIONS Patients with higher PRS for schizophrenia tended to have less improvement with antipsychotic drug treatment. PRS burden may have potential utility as a prognostic biomarker.
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Affiliation(s)
- Jian-Ping Zhang
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA,The Zucker Hillside Hospital, Division of Psychiatry Research, Northwell Health, Glen Oaks, NY, USA,The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA
| | - Delbert Robinson
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA,The Zucker Hillside Hospital, Division of Psychiatry Research, Northwell Health, Glen Oaks, NY, USA,The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA
| | - Jin Yu
- The Zucker Hillside Hospital, Division of Psychiatry Research, Northwell Health, Glen Oaks, NY, USA
| | - Juan Gallego
- Weill Cornell Medical College, NewYork-Presbyterian/Westchester Division, White Plains, NY, USA
| | | | - Rene S. Kahn
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Benedicto Crespo-Facorro
- Department of Medicine and Psychiatry, University of Cantabria, CIBERSAM, IDIVAL, University Hospital Marqués de Valdecilla, Santander, Spain
| | - Javier Vazquez-Bourgon
- Department of Medicine and Psychiatry, University of Cantabria, CIBERSAM, IDIVAL, University Hospital Marqués de Valdecilla, Santander, Spain
| | - John M. Kane
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA,The Zucker Hillside Hospital, Division of Psychiatry Research, Northwell Health, Glen Oaks, NY, USA,The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA
| | - Anil K. Malhotra
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA,The Zucker Hillside Hospital, Division of Psychiatry Research, Northwell Health, Glen Oaks, NY, USA,The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA
| | - Todd Lencz
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Departments of Psychiatry and Molecular Medicine, Hempstead, NY, USA,The Zucker Hillside Hospital, Division of Psychiatry Research, Northwell Health, Glen Oaks, NY, USA,The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA
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Anderson JS, Shade J, DiBlasi E, Shabalin AA, Docherty AR. Polygenic risk scoring and prediction of mental health outcomes. Curr Opin Psychol 2018; 27:77-81. [PMID: 30339992 DOI: 10.1016/j.copsyc.2018.09.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 09/06/2018] [Accepted: 09/14/2018] [Indexed: 02/08/2023]
Abstract
Psychiatric conditions are highly polygenic, meaning that genetic risk arises from many hundreds or thousands of genetic variants. Psychiatric genomics and psychological science are increasingly using polygenic risk scoring-the integration of all common genetic variant effects into a single risk metric-to model latent risk and to predict mental health outcomes. This review discusses the use of these scores in psychology and psychiatry to date, important methodological considerations, and potential of scoring methods for informing psychological science. Polygenic risk scores can easily be added to environmental and behavioral genetic models of latent risk, making them desirable metrics for use in psychological research.
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Affiliation(s)
- John S Anderson
- Department of Psychiatry, University of Utah School of Medicine, 201 President's Circle, Salt Lake City, UT 8412, USA
| | - Jess Shade
- Department of Psychiatry, University of Utah School of Medicine, 201 President's Circle, Salt Lake City, UT 8412, USA
| | - Emily DiBlasi
- Department of Psychiatry, University of Utah School of Medicine, 201 President's Circle, Salt Lake City, UT 8412, USA
| | - Andrey A Shabalin
- Department of Psychiatry, University of Utah School of Medicine, 201 President's Circle, Salt Lake City, UT 8412, USA; Virginia Institute for Psychiatric & Behavioral Genetics, Virginia Commonwealth University School of Medicine, 800 E. Leigh St., Biotech One Suite 100, Richmond, VA 23219, USA
| | - Anna R Docherty
- Department of Psychiatry, University of Utah School of Medicine, 201 President's Circle, Salt Lake City, UT 8412, USA; Virginia Institute for Psychiatric & Behavioral Genetics, Virginia Commonwealth University School of Medicine, 800 E. Leigh St., Biotech One Suite 100, Richmond, VA 23219, USA.
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Nucifora FC, Woznica E, Lee BJ, Cascella N, Sawa A. Treatment resistant schizophrenia: Clinical, biological, and therapeutic perspectives. Neurobiol Dis 2018; 131:104257. [PMID: 30170114 DOI: 10.1016/j.nbd.2018.08.016] [Citation(s) in RCA: 110] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 08/07/2018] [Accepted: 08/26/2018] [Indexed: 12/16/2022] Open
Abstract
Treatment resistant schizophrenia (TRS) refers to the significant proportion of schizophrenia patients who continue to have symptoms and poor outcomes despite treatment. While many definitions of TRS include failure of two different antipsychotics as a minimum criterion, the wide variability in inclusion criteria has challenged the consistency and reproducibility of results from studies of TRS. We begin by reviewing the clinical, neuroimaging, and neurobiological characteristics of TRS. We further review the current treatment strategies available, addressing clozapine, the first-line pharmacological agent for TRS, as well as pharmacological and non-pharmacological augmentation of clozapine including medication combinations, electroconvulsive therapy, repetitive transcranial magnetic stimulation, deep brain stimulation, and psychotherapies. We conclude by highlighting the most recent consensus for defining TRS proposed by the Treatment Response and Resistance in Psychosis Working Group, and provide our overview of future perspectives and directions that could help advance the field of TRS research, including the concept of TRS as a potential subtype of schizophrenia.
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Affiliation(s)
- Frederick C Nucifora
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA.
| | - Edgar Woznica
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA
| | - Brian J Lee
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA
| | - Nicola Cascella
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA
| | - Akira Sawa
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA
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Samanaite R, Gillespie A, Sendt KV, McQueen G, MacCabe JH, Egerton A. Biological Predictors of Clozapine Response: A Systematic Review. Front Psychiatry 2018; 9:327. [PMID: 30093869 PMCID: PMC6070624 DOI: 10.3389/fpsyt.2018.00327] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 06/29/2018] [Indexed: 01/04/2023] Open
Abstract
Background: Clozapine is the recommended antipsychotic for treatment-resistant schizophrenia (TRS) but there is significant variability between patients in the degree to which clozapine will improve symptoms. The biological basis of this variability is unknown. Although clozapine has efficacy in TRS, it can elicit adverse effects and initiation is often delayed. Identification of predictive biomarkers of clozapine response may aid initiation of clozapine treatment, as well as understanding of its mechanism of action. In this article we systematically review prospective or genetic studies of biological predictors of response to clozapine. Methods: We searched the PubMed database until 20th January 2018 for studies investigating "clozapine" AND ("response" OR "outcome") AND "schizophrenia." Inclusion required that studies examined a biological variable in relation to symptomatic response to clozapine. For all studies except genetic-studies, inclusion required that biological variables were measured before clozapine initiation. Results: Ninety-eight studies met the eligibility criteria and were included in the review, including neuroimaging, blood-based, cerebrospinal fluid (CSF)-based, and genetic predictors. The majority (70) are genetic studies, collectively investigating 379 different gene variants, however only three genetic variants (DRD3 Ser9Gly, HTR2A His452Tyr, and C825T GNB3) have independently replicated significant findings. Of the non-genetic variables, the most consistent predictors of a good response to clozapine are higher prefrontal cortical structural integrity and activity, and a lower ratio of the dopamine and serotonin metabolites, homovanillic acid (HVA): 5-hydroxyindoleacetic acid (5-HIAA) in CSF. Conclusions: Recommendations include that future studies should ensure adequate clozapine trial length and clozapine plasma concentrations, and may include multivariate models to increase predictive accuracy.
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Affiliation(s)
- Ruta Samanaite
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Amy Gillespie
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Kyra-Verena Sendt
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Grant McQueen
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - James H. MacCabe
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Alice Egerton
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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Mistry S, Harrison JR, Smith DJ, Escott-Price V, Zammit S. The use of polygenic risk scores to identify phenotypes associated with genetic risk of schizophrenia: Systematic review. Schizophr Res 2018; 197:2-8. [PMID: 29129507 DOI: 10.1016/j.schres.2017.10.037] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 10/27/2017] [Accepted: 10/28/2017] [Indexed: 12/12/2022]
Abstract
Studying the phenotypic manifestations of increased genetic liability for schizophrenia can increase our understanding of this disorder. Specifically, information from alleles identified in genome-wide association studies can be collapsed into a polygenic risk score (PRS) to explore how genetic risk is manifest within different samples. In this systematic review, we provide a comprehensive assessment of studies examining associations between schizophrenia PRS (SZ-PRS) and several phenotypic measures. We searched EMBASE, Medline and PsycINFO (from August 2009-14th March 2016) plus references of included studies, following PRISMA guidelines. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate. Overall, SZ-PRS was associated with increased risk for psychiatric disorders such as depression and bipolar disorder, lower performance IQ and negative symptoms. SZ-PRS explained up to 6% of genetic variation in psychiatric phenotypes, compared to <0.7% in measures of cognition. Future gains from using the PRS approach may be greater if used for examining phenotypes that are more closely related to biological substrates, for scores based on gene-pathways, and where PRSs are used to stratify individuals for study of treatment response. As it was difficult to interpret findings across studies due to insufficient information provided by many studies, we propose a framework to guide robust reporting of PRS associations in the future.
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Affiliation(s)
- Sumit Mistry
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK.
| | - Judith R Harrison
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Daniel J Smith
- Institute of Health and Wellbeing, 1 Lilybank Gardens, University of Glasgow, UK
| | - Valentina Escott-Price
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Stanley Zammit
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK; Centre for Academic Mental Health, School of Social and Community Medicine, University of Bristol, UK
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Xavier RM, Dungan JR, Keefe RS, Vorderstrasse A. Polygenic signal for symptom dimensions and cognitive performance in patients with chronic schizophrenia. Schizophr Res Cogn 2018; 12:11-19. [PMID: 29552508 PMCID: PMC5852279 DOI: 10.1016/j.scog.2018.01.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Revised: 01/13/2018] [Accepted: 01/18/2018] [Indexed: 01/04/2023]
Abstract
Genetic etiology of psychopathology symptoms and cognitive performance in schizophrenia is supported by candidate gene and polygenic risk score (PRS) association studies. Such associations are reported to be dependent on several factors - sample characteristics, illness phase, illness severity etc. We aimed to examine if schizophrenia PRS predicted psychopathology symptoms and cognitive performance in patients with chronic schizophrenia. We also examined if schizophrenia associated autosomal loci were associated with specific symptoms or cognitive domains. Case-only analysis using data from the Clinical Antipsychotics Trials of Intervention Effectiveness-Schizophrenia trials (n = 730). PRS was constructed using Psychiatric Genomics Consortium (PGC) leave one out genome wide association analysis as the discovery data set. For candidate region analysis, we selected 105-schizophrenia associated autosomal loci from the PGC study. We found a significant effect of PRS on positive symptoms at p-threshold (PT ) of 0.5 (R2 = 0.007, p = 0.029, empirical p = 0.029) and negative symptoms at PT of 1e-07 (R2 = 0.005, p = 0.047, empirical p = 0.048). For models that additionally controlled for neurocognition, best fit PRS predicted positive (p-threshold 0.01, R2 = 0.007, p = 0.013, empirical p = 0.167) and negative symptoms (p-threshold 0.1, R2 = 0.012, p = 0.004, empirical p = 0.329). No associations were seen for overall neurocognitive and social cognitive performance tests. Post-hoc analyses revealed that PRS predicted working memory and vigilance performance but did not survive correction. No candidate regions that survived multiple testing corrections were associated with either symptoms or cognitive performance. Our findings point to potentially distinct pathogenic mechanisms for schizophrenia symptoms.
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Affiliation(s)
- Rose Mary Xavier
- Neuropsychiatry Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 1034 Gates Pavilion, HUP, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | | | - Richard S.E. Keefe
- Psychiatry and Behavioral Sciences, Duke University School of Medicine, United States
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48
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Genetic correlates of insight in schizophrenia. Schizophr Res 2018; 195:290-297. [PMID: 29054485 DOI: 10.1016/j.schres.2017.10.021] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 10/09/2017] [Accepted: 10/09/2017] [Indexed: 12/15/2022]
Abstract
UNLABELLED Insight in schizophrenia is clinically important as it is associated with several adverse outcomes. Genetic contributions to insight are unknown. We examined genetic contributions to insight by investigating if polygenic risk scores (PRS) and candidate regions were associated with insight. METHOD Schizophrenia case-only analysis of the Clinical Antipsychotics Trials of Intervention Effectiveness trial. Schizophrenia PRS was constructed using Psychiatric Genomics Consortium (PGC) leave-one out GWAS as discovery data set. For candidate regions, we selected 105 schizophrenia-associated autosomal loci and 11 schizophrenia-related oligodendrocyte genes. We used regressions to examine PRS associations and set-based testing for candidate analysis. RESULTS We examined data from 730 subjects. Best-fit PRS at p-threshold of 1e-07 was associated with total insight (R2=0.005, P=0.05, empirical P=0.054) and treatment insight (R2=0.005, P=0.048, empirical P=0.048). For models that controlled for neurocognition, PRS significantly predicted treatment insight but at higher p-thresholds (0.1 to 0.5) but did not survive correction. Patients with highest polygenic burden had 5.9 times increased risk for poor insight compared to patients with lowest burden. PRS explained 3.2% (P=0.002, empirical P=0.011) of variance in poor insight. Set-based analyses identified two variants associated with poor insight- rs320703, an intergenic variant (within-set P=6e-04, FDR P=0.046) and rs1479165 in SOX2-OT (within-set P=9e-04, FDR P=0.046). CONCLUSION To the best of our knowledge, this is the first study examining genetic basis of insight. We provide evidence for genetic contributions to impaired insight. Relevance of findings and necessity for replication are discussed.
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Abstract
PURPOSE OF REVIEW Pharmacogenomics (PGx) of antipsychotic drug response is an active area of research in the past few years. We reviewed recent PGx studies with an emphasis of development of new methodologies and new research directions. RECENT FINDINGS Traditional candidate gene approach continues to generate evidence to support the associations of antipsychotic response with genes coding for drug targets such as DRD2. Genome-wide association studies have found a few novel genes that may be associated with drug efficacy and adverse events. Recent application of polygenic risk score makes it possible to combine many genetic variants to predict clinical response. Finally, epigenetic research including DNA methylation is emerging and promises new findings that potentially can be applied in clinical practice. New methodologies may advance PGx closer to clinical application. Multiple genes and epigenomic markers can be used in prediction of clinical phenotypes.
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Affiliation(s)
- Jian-Ping Zhang
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY, USA.
- Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, 75-59 263rd Street, Glen Oaks, NY, 11004, USA.
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA.
| | - Anil K Malhotra
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY, USA.
- Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, 75-59 263rd Street, Glen Oaks, NY, 11004, USA.
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA.
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Li J, Yoshikawa A, Brennan MD, Ramsey TL, Meltzer HY. Genetic predictors of antipsychotic response to lurasidone identified in a genome wide association study and by schizophrenia risk genes. Schizophr Res 2018; 192:194-204. [PMID: 28431800 DOI: 10.1016/j.schres.2017.04.009] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2017] [Revised: 03/31/2017] [Accepted: 04/02/2017] [Indexed: 12/23/2022]
Abstract
Biomarkers which predict response to atypical antipsychotic drugs (AAPDs) increases their benefit/risk ratio. We sought to identify common variants in genes which predict response to lurasidone, an AAPD, by associating genome-wide association study (GWAS) data and changes (Δ) in Positive And Negative Syndrome Scale (PANSS) scores from two 6-week randomized, placebo-controlled trials of lurasidone in schizophrenia (SCZ) patients. We also included SCZ risk SNPs identified by the Psychiatric Genomics Consortium using a polygenic risk analysis. The top genomic loci, with uncorrected p<10-4, include: 1) synaptic adhesion (PTPRD, LRRC4C, NRXN1, ILIRAPL1, SLITRK1) and scaffolding (MAGI1, MAGI2, NBEA) genes, both essential for synaptic function; 2) other synaptic plasticity-related genes (NRG1/3 and KALRN); 3) the neuron-specific RNA splicing regulator, RBFOX1; and 4) ion channel genes, e.g. KCNA10, KCNAB1, KCNK9 and CACNA2D3). Some genes predicted response for patients with both European and African Ancestries. We replicated some SNPs reported to predict response to other atypical APDs in other GWAS. Although none of the biomarkers reached genome-wide significance, many of the genes and associated pathways have previously been linked to SCZ. Two polygenic modeling approaches, GCTA-GREML and PLINK-Polygenic Risk Score, demonstrated that some risk genes related to neurodevelopment, synaptic biology, immune response, and histones, also contributed to prediction of response. The top hits predicting response to lurasidone did not predict improvement with placebo. This is the first evidence from clinical trials that SCZ risk SNPs are related to clinical response to an AAPD. These results need to be replicated in an independent sample.
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Affiliation(s)
- Jiang Li
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, USA
| | - Akane Yoshikawa
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, USA
| | | | | | - Herbert Y Meltzer
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, USA.
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