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Ibragimov K, Keane GP, Carreño Glaría C, Cheng J, Llosa AE. Haloperidol (oral) versus olanzapine (oral) for people with schizophrenia and schizophrenia-spectrum disorders. Cochrane Database Syst Rev 2024; 7:CD013425. [PMID: 38958149 PMCID: PMC11220909 DOI: 10.1002/14651858.cd013425.pub2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/04/2024]
Abstract
BACKGROUND Schizophrenia is often a severe and disabling psychiatric disorder. Antipsychotics remain the mainstay of psychotropic treatment for people with psychosis. In limited resource and humanitarian contexts, it is key to have several options for beneficial, low-cost antipsychotics, which require minimal monitoring. We wanted to compare oral haloperidol, as one of the most available antipsychotics in these settings, with a second-generation antipsychotic, olanzapine. OBJECTIVES To assess the clinical benefits and harms of haloperidol compared to olanzapine for people with schizophrenia and schizophrenia-spectrum disorders. SEARCH METHODS We searched the Cochrane Schizophrenia study-based register of trials, which is based on monthly searches of CENTRAL, CINAHL, ClinicalTrials.gov, Embase, ISRCTN, MEDLINE, PsycINFO, PubMed and WHO ICTRP. We screened the references of all included studies. We contacted relevant authors of trials for additional information where clarification was required or where data were incomplete. The register was last searched on 14 January 2023. SELECTION CRITERIA Randomised clinical trials comparing haloperidol with olanzapine for people with schizophrenia and schizophrenia-spectrum disorders. Our main outcomes of interest were clinically important change in global state, relapse, clinically important change in mental state, extrapyramidal side effects, weight increase, clinically important change in quality of life and leaving the study early due to adverse effects. DATA COLLECTION AND ANALYSIS We independently evaluated and extracted data. For dichotomous outcomes, we calculated risk ratios (RR) and their 95% confidence intervals (CI) and the number needed to treat for an additional beneficial or harmful outcome (NNTB or NNTH) with 95% CI. For continuous data, we estimated mean differences (MD) or standardised mean differences (SMD) with 95% CIs. For all included studies, we assessed risk of bias (RoB 1) and we used the GRADE approach to create a summary of findings table. MAIN RESULTS We included 68 studies randomising 9132 participants. We are very uncertain whether there is a difference between haloperidol and olanzapine in clinically important change in global state (RR 0.84, 95% CI 0.69 to 1.02; 6 studies, 3078 participants; very low-certainty evidence). We are very uncertain whether there is a difference between haloperidol and olanzapine in relapse (RR 1.42, 95% CI 1.00 to 2.02; 7 studies, 1499 participants; very low-certainty evidence). Haloperidol may reduce the incidence of clinically important change in overall mental state compared to olanzapine (RR 0.70, 95% CI 0.60 to 0.81; 13 studies, 1210 participants; low-certainty evidence). For every eight people treated with haloperidol instead of olanzapine, one fewer person would experience this improvement. The evidence suggests that haloperidol may result in a large increase in extrapyramidal side effects compared to olanzapine (RR 3.38, 95% CI 2.28 to 5.02; 14 studies, 3290 participants; low-certainty evidence). For every three people treated with haloperidol instead of olanzapine, one additional person would experience extrapyramidal side effects. For weight gain, the evidence suggests that there may be a large reduction in the risk with haloperidol compared to olanzapine (RR 0.47, 95% CI 0.35 to 0.61; 18 studies, 4302 participants; low-certainty evidence). For every 10 people treated with haloperidol instead of olanzapine, one fewer person would experience weight increase. A single study suggests that haloperidol may reduce the incidence of clinically important change in quality of life compared to olanzapine (RR 0.72, 95% CI 0.57 to 0.91; 828 participants; low-certainty evidence). For every nine people treated with haloperidol instead of olanzapine, one fewer person would experience clinically important improvement in quality of life. Haloperidol may result in an increase in the incidence of leaving the study early due to adverse effects compared to olanzapine (RR 1.99, 95% CI 1.60 to 2.47; 21 studies, 5047 participants; low-certainty evidence). For every 22 people treated with haloperidol instead of olanzapine, one fewer person would experience this outcome. Thirty otherwise relevant studies and several endpoints from 14 included studies could not be evaluated due to inconsistencies and poor transparency of several parameters. Furthermore, even within studies that were included, it was often not possible to use data for the same reasons. Risk of bias differed substantially for different outcomes and the certainty of the evidence ranged from very low to low. The most common risks of bias leading to downgrading of the evidence were blinding (performance bias) and selective reporting (reporting bias). AUTHORS' CONCLUSIONS Overall, the certainty of the evidence was low to very low for the main outcomes in this review, making it difficult to draw reliable conclusions. We are very uncertain whether there is a difference between haloperidol and olanzapine in terms of clinically important global state and relapse. Olanzapine may result in a slightly greater overall clinically important change in mental state and in a clinically important change in quality of life. Different side effect profiles were noted: haloperidol may result in a large increase in extrapyramidal side effects and olanzapine in a large increase in weight gain. The drug of choice needs to take into account side effect profiles and the preferences of the individual. These findings and the recent inclusion of olanzapine alongside haloperidol in the WHO Model List of Essential Medicines should increase the likelihood of it becoming more easily available in low- and middle- income countries, thereby improving choice and providing a greater ability to respond to side effects for people with lived experience of schizophrenia. There is a need for additional research using appropriate and equivalent dosages of these drugs. Some of this research needs to be done in low- and middle-income settings and should actively seek to account for factors relevant to these. Research on antipsychotics needs to be person-centred and prioritise factors that are of interest to people with lived experience of schizophrenia.
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Affiliation(s)
- Khasan Ibragimov
- Ecole des Hautes Etudes en Sante Publique (EHESP), Hautes Etudes en Sante Publique (EHESP), Paris, France
- Epicentre, Paris, France
| | | | | | - Jie Cheng
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Augusto Eduardo Llosa
- Epicentre, Paris, France
- Operational Centre Barcelona, Médecins Sans Frontières, Barcelona, Spain
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Chen S, Tang D, Deng L, Xu S. Asian-European differentiation of schizophrenia-associated genes driven by admixture and natural selection. iScience 2024; 27:109560. [PMID: 38638564 PMCID: PMC11024917 DOI: 10.1016/j.isci.2024.109560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/29/2023] [Accepted: 03/22/2024] [Indexed: 04/20/2024] Open
Abstract
The European-centered genome-wide association studies of schizophrenia (SCZ) may not be well applied to non-European populations. We analyzed 1,592 reported SCZ-associated genes using the public genome data and found an overall higher Asian-European differentiation on the SCZ-associated variants than at the genome-wide level. Notable examples included 15 missense variants, a regulatory variant SLC5A10-rs1624825, and a damaging variant TSPAN18-rs1001292. Independent local adaptations in recent 25,000 years, after the Asian-European divergence, could have contributed to such genetic differentiation, as were identified at a missense mutation LTN1-rs57646126-A in Asians, and a non-risk allele ZSWIM6-rs72761442-G in Europeans. Altai-Neanderthal-derived alleles may have opposite effects on SCZ susceptibility between ancestries. Furthermore, adaptive introgression was detected on the non-risk haplotype at 1q21.2 in Europeans, while in Asians it was observed on the SCZ risk haplotype at 3p21.31 which is also potentially ultra-violet protective. This study emphasizes the importance of including more representative Asian samples in future SCZ studies.
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Affiliation(s)
- Sihan Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Die Tang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Lian Deng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China
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Peng Y, Tao Y, Liu L, Zhang J, Wei B. Crosstalk among Reactive Oxygen Species, Autophagy and Metabolism in Myocardial Ischemia and Reperfusion Stages. Aging Dis 2024; 15:1075-1107. [PMID: 37728583 PMCID: PMC11081167 DOI: 10.14336/ad.2023.0823-4] [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: 07/03/2023] [Accepted: 08/23/2023] [Indexed: 09/21/2023] Open
Abstract
Myocardial ischemia is the most common cardiovascular disease. Reperfusion, an important myocardial ischemia tool, causes unexpected and irreversible damage to cardiomyocytes, resulting in myocardial ischemia/reperfusion (MI/R) injury. Upon stress, especially oxidative stress induced by reactive oxygen species (ROS), autophagy, which degrades the intracellular energy storage to produce metabolites that are recycled into metabolic pathways to buffer metabolic stress, is initiated during myocardial ischemia and MI/R injury. Excellent cardioprotective effects of autophagy regulators against MI and MI/R have been reported. Reversing disordered cardiac metabolism induced by ROS also exhibits cardioprotective action in patients with myocardial ischemia. Herein, we review current knowledge on the crosstalk between ROS, cardiac autophagy, and metabolism in myocardial ischemia and MI/R. Finally, we discuss the possible regulators of autophagy and metabolism that can be exploited to harness the therapeutic potential of cardiac metabolism and autophagy in the diagnosis and treatment of myocardial ischemia and MI/R.
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Affiliation(s)
- Yajie Peng
- Key Laboratory of Advanced Pharmaceutical Technology, Ministry of Education of China; School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan, China.
| | - Yachuan Tao
- Key Laboratory of Advanced Pharmaceutical Technology, Ministry of Education of China; School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan, China.
- Department of Pharmacology, School of Pharmaceutical Sciences, Fudan University, Shanghai, China
| | - Lingxu Liu
- Key Laboratory of Advanced Pharmaceutical Technology, Ministry of Education of China; School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan, China.
| | - Ji Zhang
- The First Affiliated Hospital of Zhengzhou University, Department of Pharmacy, Zhengzhou, Henan, China.
| | - Bo Wei
- Key Laboratory of Advanced Pharmaceutical Technology, Ministry of Education of China; School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan, China.
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Hernandez M, Cullell N, Cendros M, Serra-Llovich A, Arranz MJ. Clinical Utility and Implementation of Pharmacogenomics for the Personalisation of Antipsychotic Treatments. Pharmaceutics 2024; 16:244. [PMID: 38399298 PMCID: PMC10893329 DOI: 10.3390/pharmaceutics16020244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 01/24/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024] Open
Abstract
Decades of pharmacogenetic research have revealed genetic biomarkers of clinical response to antipsychotics. Genetic variants in antipsychotic targets, dopamine and serotonin receptors in particular, and in metabolic enzymes have been associated with the efficacy and toxicity of antipsychotic treatments. However, genetic prediction of antipsychotic response based on these biomarkers is far from accurate. Despite the clinical validity of these findings, the clinical utility remains unclear. Nevertheless, genetic information on CYP metabolic enzymes responsible for the biotransformation of most commercially available antipsychotics has proven to be effective for the personalisation of clinical dosing, resulting in a reduction of induced side effects and in an increase in efficacy. However, pharmacogenetic information is rarely used in psychiatric settings as a prescription aid. Lack of studies on cost-effectiveness, absence of clinical guidelines based on pharmacogenetic biomarkers for several commonly used antipsychotics, the cost of genetic testing and the delay in results delivery hamper the implementation of pharmacogenetic interventions in clinical settings. This narrative review will comment on the existing pharmacogenetic information, the clinical utility of pharmacogenetic findings, and their current and future implementations.
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Affiliation(s)
- Marta Hernandez
- PHAGEX Research Group, University Ramon Llull, 08022 Barcelona, Spain;
- School of Health Sciences Blanquerna, University Ramon Llull, 08022 Barcelona, Spain
| | - Natalia Cullell
- Fundació Docència i Recerca Mútua Terrassa, 08221 Terrassa, Spain; (N.C.); (A.S.-L.)
- Department of Neurology, Hospital Universitari Mútua Terrassa, 08221 Terrassa, Spain
| | - Marc Cendros
- EUGENOMIC Genómica y Farmacogenética, 08029 Barcelona, Spain;
| | | | - Maria J. Arranz
- PHAGEX Research Group, University Ramon Llull, 08022 Barcelona, Spain;
- Fundació Docència i Recerca Mútua Terrassa, 08221 Terrassa, Spain; (N.C.); (A.S.-L.)
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Cuomo A, Barillà G, Serafini G, Aguglia A, Amerio A, Cattolico M, Carmellini P, Spiti A, Fagiolini A. Drug-drug interactions between COVID-19 therapeutics and psychotropic medications. Expert Opin Drug Metab Toxicol 2023; 19:925-936. [PMID: 38032183 DOI: 10.1080/17425255.2023.2288681] [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: 05/29/2023] [Accepted: 11/23/2023] [Indexed: 12/01/2023]
Abstract
INTRODUCTION The coronavirus (COVID-19) pandemic has led to as well as exacerbated mental health disorders, leading to increased use of psychotropic medications. Co-administration of COVID-19 and psychotropic medications may result in drug-drug interactions (DDIs), that may compromise both the safety and efficacy of both medications. AREAS COVERED This review provides an update of the current evidence on DDIs between COVID-19 and psychotropic medications. The interactions are categorized into pharmacokinetic, pharmacodynamic, and other relevant types. A thorough literature search was conducted using electronic databases to identify relevant studies, and extract data to highlight potential DDIs, clinical implications, and management strategies. EXPERT OPINION Understanding and managing potential DDIs between COVID-19 and psychotropic medications is paramount to ensuring safe and effective treatment of patients with COVID-19 and mental illness. Awareness of the diverse spectrum of DDIs, vigilant monitoring, and judicious dose modifications, while choosing pharmacotherapeutic options with low risk of interaction whenever possible, are necessary. Ongoing and future investigations should continue to review the dynamic landscape of COVID-19 therapeutic modalities and their interactions with psychotropic medications.
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Affiliation(s)
- Alessandro Cuomo
- Division of Psychiatry, Department of Molecular Medicine University of Siena School of Medicine Siena, Siena, Italy
| | - Giovanni Barillà
- Division of Psychiatry, Department of Molecular Medicine University of Siena School of Medicine Siena, Siena, Italy
| | - Gianluca Serafini
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Section of Psychiatry, University of Genoa, Genoa, Italy
- Department of Neuroscience, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Andrea Aguglia
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Section of Psychiatry, University of Genoa, Genoa, Italy
- Department of Neuroscience, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Andrea Amerio
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Section of Psychiatry, University of Genoa, Genoa, Italy
- Department of Neuroscience, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Matteo Cattolico
- Division of Psychiatry, Department of Molecular Medicine University of Siena School of Medicine Siena, Siena, Italy
| | - Pietro Carmellini
- Division of Psychiatry, Department of Molecular Medicine University of Siena School of Medicine Siena, Siena, Italy
| | - Alessandro Spiti
- Division of Psychiatry, Department of Molecular Medicine University of Siena School of Medicine Siena, Siena, Italy
| | - Andrea Fagiolini
- Division of Psychiatry, Department of Molecular Medicine University of Siena School of Medicine Siena, Siena, Italy
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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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Lu Z, Zhang Y, Sun Y, Liao Y, Kang Z, Feng X, Yan H, Wang L, Lu T, Zhang D, Yue W. Therapeutic outcomes wide association scan of different antipsychotics in patients with schizophrenia: Randomized clinical trials and multi-ancestry validation. Psychiatry Clin Neurosci 2023; 77:486-496. [PMID: 37210704 DOI: 10.1111/pcn.13567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 05/05/2023] [Accepted: 05/15/2023] [Indexed: 05/22/2023]
Abstract
AIM This study identified discrepant therapeutic outcomes of antipsychotics. METHODS A total of 5191 patients with schizophrenia were enrolled, 3030 as discovery cohort, 1395 as validation cohort, and 766 as multi-ancestry validation cohort. Therapeutic Outcomes Wide Association Scan was conducted. Types of antipsychotics (one antipsychotic vs other antipsychotics) were dependent variables, therapeutic outcomes including efficacy and safety were independent variables. RESULTS In discovery cohort, olanzapine related to higher risk of weight gain (AIWG, OR: 2.21-2.86), liver dysfunction (OR: 1.75-2.33), sedation (OR: 1.76-2.86), increased lipid level (OR: 2.04-2.12), and lower risk of extrapyramidal syndrome (EPS, OR: 0.14-0.46); risperidone related to higher risk of hyperprolactinemia (OR: 12.45-20.53); quetiapine related to higher risk of sedation (OR = 1.73), palpitation (OR = 2.87), increased lipid level (OR = 1.69), lower risk of hyperprolactinemia (OR: 0.09-0.11), and EPS (OR: 0.15-0.44); aripiprazole related to lower risk of hyperprolactinemia (OR: 0.09-0.14), AIWG (OR = 0.44), sedation (OR: 0.33-0.47), and QTc prolongation (β = -2.17); ziprasidone related to higher risk of increased QT interval (β range: 3.11-3.22), nausea (OR: 3.22-3.91), lower risk of AIWG (OR: 0.27-0.46), liver dysfunction (OR: 0.41-0.38), and increased lipid level (OR: 0.41-0.55); haloperidol related to higher risk of EPS (OR: 2.64-6.29), hyperprolactinemia (OR: 5.45-9.44), and increased salivation (OR: 3.50-3.68). Perphenazine related to higher risk of EPS (OR: 1.89-2.54). Higher risk of liver dysfunction in olanzapine and lower risk of hyperprolactinemia in aripiprazole were confirmed in validation cohort, and higher risk of AIWG in olanzapine and hyperprolactinemia in risperidone were confirmed in multi-ancestry validation cohort. CONCLUSION Future precision medicine should focus on personalized side-effects.
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Affiliation(s)
- Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Yaoyao Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Yundan Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Zhewei Kang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Xiaoyang Feng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Lifang Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Dai Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
- NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
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Lu Z, Zhang Y, Sun Y, Liao Y, Kang Z, Feng X, Yan H, Li J, Wang L, Lu T, Zhang D, Huang Y, Yue W. The positive association between antipsychotic-induced weight gain and therapeutic response: New biotypes of schizophrenia. Psychiatry Res 2023; 324:115226. [PMID: 37116323 DOI: 10.1016/j.psychres.2023.115226] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 04/14/2023] [Accepted: 04/23/2023] [Indexed: 04/30/2023]
Abstract
Co-occurrence of antipsychotic-induced weight gain (AIWG) and therapeutic response (TR) did exist in clinic but was rarely studied. This study aims to identify potential TR/ AIWG biotypes and explore the clinical, genetic and neuroimaging features. This study enrolled 3030 patients to identify potential TR/AIWG biotypes and explore the clinical, genetic and neuroimaging features. We found three biotypes: TR+nonAIWG (46.91%), TR+AIWG (18.82%), and nonTR+nonAIWG (34.27%). TR+AIWG showed lower weight and lipid level at baseline, but higher changing rate, and higher genetic risk of obesity than TR+nonAIWG and nonTR+nonAIWG. GWAS identified ADIPOQ gene related to TR+AIWG biotypes and top-ranked loci enriched in one-carbon metabolic process, which related to both schizophrenia and metabolic dysfunction. Genetically predicted TR+AIWG was associated with higher odds of diabetes (OR=1.05). The left supplementary motor area was significantly negatively correlated with PRS of obesity. The distinguishing ability with multi-omics data to identify TR+AIWG reached 0.787. In a word, the "thin" patients with a higher risk of obesity are the target population of early intervention.
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Affiliation(s)
- Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Yaoyao Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Yundan Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Zhewei Kang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Xiaoyang Feng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Jun Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Lifang Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China
| | - Dai Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China; PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China; Chinese Institute for Brain Research, Beijing 102206, China
| | - Yu Huang
- National Engineering Research Center for Software Engineering, Peking University, Beijing 100871, China.
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; NHC Key Laboratory of Mental Health (Peking University), Beijing 100191, China; PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China; Chinese Institute for Brain Research, Beijing 102206, China.
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Binding mechanism of perphenazine/thioridazine with acetylcholinesterase: Spectroscopic surface plasmon resonance and molecular docking based analysis. J Mol Liq 2023. [DOI: 10.1016/j.molliq.2023.121547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
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Toba-Oluboka T, Tibbo PG, Dempster K, Alda M. Genetic factors contribute to medication-induced QT prolongation: A review. Psychiatry Res 2022; 317:114891. [PMID: 36257205 DOI: 10.1016/j.psychres.2022.114891] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 09/21/2022] [Accepted: 10/07/2022] [Indexed: 01/05/2023]
Abstract
QT prolongation is a heart rhythm condition that impacts the lives of many people and when severe can be life-threatening. QT prolongation has been linked to variations in several genes, but it can also arise in the course of treatments with medications such as certain antipsychotics and antidepressants. However, it is unclear whether the risk of medication-induced QT prolongation (MIQTP) depends on specific genetic vulnerability. Here, we review the available literature on the interplay between genetic risk and medication exposure in the context of psychiatric treatment. A review was conducted on the genetic contribution to MIQTP in psychiatric patients. A literature search was conducted on the PubMed platform with 8 papers meeting criteria for review. A total of 3,838 patients from 8 studies meeting criteria for a psychotic or mood disorder were included in this review. All studies found evidence for the genetic contribution to MIQTP. The specific genes identified in these studies included the NOS1AP, ABCB1, KCNH2, SLC22A23, EPB41L4A, LEP, CACNA1C, CERKL, SLCO3A1, BRUNOL4, NRG3, NUBPL, PALLD, NDRG4 and PLN genes. The findings highlight both the importance of monitoring heart parameters in psychiatry and the possible role for genetic profiling to increase the treatment safety.
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Affiliation(s)
- Temi Toba-Oluboka
- Department of Psychiatry, Early Psychosis Research, Dalhousie University, Unit Room 4083A AJLB, 5909 Veterans' Memorial Lane, Halifax, NS, Canada.
| | - Philip G Tibbo
- Department of Psychiatry, Early Psychosis Research, Dalhousie University, Unit Room 4083A AJLB, 5909 Veterans' Memorial Lane, Halifax, NS, Canada
| | - Kara Dempster
- Department of Psychiatry, Early Psychosis Research, Dalhousie University, Unit Room 4083A AJLB, 5909 Veterans' Memorial Lane, Halifax, NS, Canada
| | - Martin Alda
- Department of Psychiatry, Early Psychosis Research, Dalhousie University, Unit Room 4083A AJLB, 5909 Veterans' Memorial Lane, Halifax, NS, Canada
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