Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data
Antipsychotics (APs) are associated with weight gain and other metabolic abnormalities such as hyperglycemia, dyslipidemia and metabolic syndrome. This translational study aimed to uncover the underlying molecular mechanisms and identify the key genes involved in AP-induced metabolic effects. An int...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-08-01
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| Series: | Frontiers in Pharmacology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2021.729474/full |
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| author | Albert Martínez-Pinteño Patricia Gassó Patricia Gassó Patricia Gassó Llucia Prohens Alex G. Segura Mara Parellada Mara Parellada Jerónimo Saiz-Ruiz Jerónimo Saiz-Ruiz Manuel J. Cuesta Manuel J. Cuesta Miguel Bernardo Miguel Bernardo Miguel Bernardo Miguel Bernardo Amalia Lafuente Amalia Lafuente Amalia Lafuente Sergi Mas Sergi Mas Sergi Mas Natalia Rodríguez |
| author_facet | Albert Martínez-Pinteño Patricia Gassó Patricia Gassó Patricia Gassó Llucia Prohens Alex G. Segura Mara Parellada Mara Parellada Jerónimo Saiz-Ruiz Jerónimo Saiz-Ruiz Manuel J. Cuesta Manuel J. Cuesta Miguel Bernardo Miguel Bernardo Miguel Bernardo Miguel Bernardo Amalia Lafuente Amalia Lafuente Amalia Lafuente Sergi Mas Sergi Mas Sergi Mas Natalia Rodríguez |
| author_sort | Albert Martínez-Pinteño |
| collection | DOAJ |
| description | Antipsychotics (APs) are associated with weight gain and other metabolic abnormalities such as hyperglycemia, dyslipidemia and metabolic syndrome. This translational study aimed to uncover the underlying molecular mechanisms and identify the key genes involved in AP-induced metabolic effects. An integrative gene expression analysis was performed in four different mouse tissues (striatum, liver, pancreas and adipose) after risperidone or olanzapine treatment. The analytical approach combined the identification of the gene co-expression modules related to AP treatment, gene set enrichment analysis and protein-protein interaction network construction. We found several co-expression modules of genes involved in glucose and lipid homeostasis, hormone regulation and other processes related to metabolic impairment. Among these genes, EP300, which encodes an acetyltransferase involved in transcriptional regulation, was identified as the most important hub gene overlapping the networks of both APs. Then, we explored the genetically predicted EP300 expression levels in a cohort of 226 patients with first-episode psychosis who were being treated with APs to further assess the association of this gene with metabolic alterations. The EP300 expression levels were significantly associated with increases in body weight, body mass index, total cholesterol levels, low-density lipoprotein cholesterol levels and triglyceride concentrations after 6 months of AP treatment. Taken together, our analysis identified EP300 as a key gene in AP-induced metabolic abnormalities, indicating that the dysregulation of EP300 function could be important in the development of these side effects. However, more studies are needed to disentangle the role of this gene in the mechanism of action of APs. |
| first_indexed | 2024-12-22T16:04:31Z |
| format | Article |
| id | doaj.art-05652b2e8938444fa91c73adb12bc746 |
| institution | Directory Open Access Journal |
| issn | 1663-9812 |
| language | English |
| last_indexed | 2024-12-22T16:04:31Z |
| publishDate | 2021-08-01 |
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| series | Frontiers in Pharmacology |
| spelling | doaj.art-05652b2e8938444fa91c73adb12bc7462022-12-21T18:20:37ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122021-08-011210.3389/fphar.2021.729474729474Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression DataAlbert Martínez-Pinteño0Patricia Gassó1Patricia Gassó2Patricia Gassó3Llucia Prohens4Alex G. Segura5Mara Parellada6Mara Parellada7Jerónimo Saiz-Ruiz8Jerónimo Saiz-Ruiz9Manuel J. Cuesta10Manuel J. Cuesta11Miguel Bernardo12Miguel Bernardo13Miguel Bernardo14Miguel Bernardo15Amalia Lafuente16Amalia Lafuente17Amalia Lafuente18Sergi Mas19Sergi Mas20Sergi Mas21Natalia Rodríguez22Department of Basic Clinical Practice, Pharmacology Unit, University of Barcelona, Barcelona, SpainDepartment of Basic Clinical Practice, Pharmacology Unit, University of Barcelona, Barcelona, SpainInstitut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, SpainCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, SpainDepartment of Basic Clinical Practice, Pharmacology Unit, University of Barcelona, Barcelona, SpainDepartment of Basic Clinical Practice, Pharmacology Unit, University of Barcelona, Barcelona, SpainCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, SpainDepartment of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, Madrid, SpainCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, SpainDepartment of Psychiatry, Hospital Universitario Ramón y Cajal, IRYCIS, Universidad de Alcalá, Madrid, SpainCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, SpainDepartment of Psychiatry, Complejo Hospitalario de Navarra, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, SpainInstitut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, SpainCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, SpainBarcelona Clínic Schizophrenia Unit, Hospital Clínic de Barcelona, Barcelona, SpainDepartment of Medicine, University of Barcelona, Barcelona, SpainDepartment of Basic Clinical Practice, Pharmacology Unit, University of Barcelona, Barcelona, SpainInstitut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, SpainCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, SpainDepartment of Basic Clinical Practice, Pharmacology Unit, University of Barcelona, Barcelona, SpainInstitut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, SpainCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, SpainDepartment of Basic Clinical Practice, Pharmacology Unit, University of Barcelona, Barcelona, SpainAntipsychotics (APs) are associated with weight gain and other metabolic abnormalities such as hyperglycemia, dyslipidemia and metabolic syndrome. This translational study aimed to uncover the underlying molecular mechanisms and identify the key genes involved in AP-induced metabolic effects. An integrative gene expression analysis was performed in four different mouse tissues (striatum, liver, pancreas and adipose) after risperidone or olanzapine treatment. The analytical approach combined the identification of the gene co-expression modules related to AP treatment, gene set enrichment analysis and protein-protein interaction network construction. We found several co-expression modules of genes involved in glucose and lipid homeostasis, hormone regulation and other processes related to metabolic impairment. Among these genes, EP300, which encodes an acetyltransferase involved in transcriptional regulation, was identified as the most important hub gene overlapping the networks of both APs. Then, we explored the genetically predicted EP300 expression levels in a cohort of 226 patients with first-episode psychosis who were being treated with APs to further assess the association of this gene with metabolic alterations. The EP300 expression levels were significantly associated with increases in body weight, body mass index, total cholesterol levels, low-density lipoprotein cholesterol levels and triglyceride concentrations after 6 months of AP treatment. Taken together, our analysis identified EP300 as a key gene in AP-induced metabolic abnormalities, indicating that the dysregulation of EP300 function could be important in the development of these side effects. However, more studies are needed to disentangle the role of this gene in the mechanism of action of APs.https://www.frontiersin.org/articles/10.3389/fphar.2021.729474/fullantipsychoticsweight gainmetabolic syndromepharmacogeneticsEP300gene |
| spellingShingle | Albert Martínez-Pinteño Patricia Gassó Patricia Gassó Patricia Gassó Llucia Prohens Alex G. Segura Mara Parellada Mara Parellada Jerónimo Saiz-Ruiz Jerónimo Saiz-Ruiz Manuel J. Cuesta Manuel J. Cuesta Miguel Bernardo Miguel Bernardo Miguel Bernardo Miguel Bernardo Amalia Lafuente Amalia Lafuente Amalia Lafuente Sergi Mas Sergi Mas Sergi Mas Natalia Rodríguez Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data Frontiers in Pharmacology antipsychotics weight gain metabolic syndrome pharmacogenetics EP300 gene |
| title | Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data |
| title_full | Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data |
| title_fullStr | Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data |
| title_full_unstemmed | Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data |
| title_short | Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data |
| title_sort | identification of ep300 as a key gene involved in antipsychotic induced metabolic dysregulation based on integrative bioinformatics analysis of multi tissue gene expression data |
| topic | antipsychotics weight gain metabolic syndrome pharmacogenetics EP300 gene |
| url | https://www.frontiersin.org/articles/10.3389/fphar.2021.729474/full |
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