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Müller S, Lieb K, Streit F, Awasthi S, Wagner S, Frank J, Müller MB, Tadic A, Heilmann-Heimbach S, Hoffmann P, Mavarani L, Schmidt B, Rietschel M, Witt SH, Zillich L, Engelmann J. Common polygenic variation in the early medication change (EMC) cohort affects disorder risk, but not the antidepressant treatment response. J Affect Disord 2024; 363:542-551. [PMID: 39038621 DOI: 10.1016/j.jad.2024.07.138] [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: 01/29/2024] [Revised: 07/08/2024] [Accepted: 07/16/2024] [Indexed: 07/24/2024]
Abstract
BACKGROUND Given the great interest in identifying reliable predictors of the response to antidepressant drugs, the present study investigated whether polygenic scores (PGS) for Major Depressive Disorder (MDD) and antidepressant treatment response (ADR) were related to the complex trait of antidepressant response in the Early Medication Change (EMC) cohort. METHODS In this secondary analysis of the EMC trial (N = 889), 481 MDD patients were included and compared to controls from a population-based cohort. Patients were treated over eight weeks within a pre-defined treatment-algorithm. We investigated patients' genetic variation associated with MDD and ADR, using PGS and examined the association of PGS with treatment outcomes (early improvement, response, remission). Additionally, the influence of two cytochrome P450 drug-metabolizing enzymes (CYP2C19, CYP2D6) was determined. RESULTS PGS for MDD was significantly associated with disorder status (NkR2 = 2.48 %, p < 1*10-12), with higher genetic burden in EMC patients compared to controls. The PGS for ADR did not explain remission status. The PGS for MDD and ADR were also not associated with treatment outcomes. In addition, there were no effects of common CYP450 gene variants on ADR. LIMITATIONS The study was limited by variability in the outcome parameters due to differences in treatment and insufficient sample size in the used ADR genome-wide association study (GWAS). CONCLUSIONS The present study confirms a polygenic contribution to MDD burden in the EMC patients. Larger GWAS with homogeneity in antidepressant treatments are needed to explore the genetic variation associated with ADR and realize the potential of PGS to contribute to specific response subtypes.
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Affiliation(s)
- Svenja Müller
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; German Center for Mental Health (DZPG), Partner site Mannheim/Heidelberg/Ulm, Germany.
| | - Klaus Lieb
- Department of Psychiatry and Psychotherapy, University Medical Center, Mainz, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; German Center for Mental Health (DZPG), Partner site Mannheim/Heidelberg/Ulm, Germany; Hector Institute for Artificial Intelligence in Psychiatry (HITKIP), Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Swapnil Awasthi
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
| | - Stefanie Wagner
- Department of Psychiatry and Psychotherapy, University Medical Center, Mainz, Germany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Marianne B Müller
- Department of Psychiatry and Psychotherapy, University Medical Center, Mainz, Germany; Translational Psychiatry, Department of Psychiatry and Psychotherapy & Focus Program Translational Neuroscience, University Medical Center, Mainz, Germany
| | - André Tadic
- Department of Psychiatry and Psychotherapy, University Medical Center, Mainz, Germany; Department of Psychiatry, Psychosomatics, and Psychotherapy, DR. FONTHEIM Mentale Gesundheit, Liebenburg, Germany
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Laven Mavarani
- Institute for Medical Informatics, Biometry and Epidemiology, University Duisburg-Essen, Essen, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University Duisburg-Essen, Essen, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; German Center for Mental Health (DZPG), Partner site Mannheim/Heidelberg/Ulm, Germany
| | - Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; German Center for Mental Health (DZPG), Partner site Mannheim/Heidelberg/Ulm, Germany
| | - Jan Engelmann
- Department of Psychiatry and Psychotherapy, University Medical Center, Mainz, Germany; Translational Psychiatry, Department of Psychiatry and Psychotherapy & Focus Program Translational Neuroscience, University Medical Center, Mainz, Germany.
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Yang L, Su Y, Dong S, Wu T, Zhang Y, Qiu H, Gu W, Qiu H, Xu Y, Wang J, Chen J, Fang Y. Concordance of the treatment patterns for major depressive disorders between the Canadian Network for Mood and Anxiety Treatments (CANMAT) algorithm and real-world practice in China. Front Pharmacol 2022; 13:954973. [PMID: 36120331 PMCID: PMC9471191 DOI: 10.3389/fphar.2022.954973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 08/08/2022] [Indexed: 12/04/2022] Open
Abstract
Background: Antidepressant (AD) algorithm is an important tool to support treatment decision-making and improve management of major depressive disorder (MDD). However, little is known about its concordance with real-world practice. This study aimed to assess the concordance between the longitudinal treatment patterns and AD algorithm recommended by a clinical practice guideline in China. Methods: Data were obtained from the electronic medical records of Shanghai Mental Health Center (SMHC), one of the largest mental health institutions in China. We examined the concordance between clinical practice and the Canadian Network for Mood and Anxiety Treatments (CANMAT) algorithm among a cohort composed of 19,955 MDD patients. The longitudinal characteristics of treatment regimen and duration were described to identify the specific inconsistencies. Demographics and health utilizations of the algorithm-concordant and -discordant subgroups with optimized treatment were measured separately. Results: The overall proportion of algorithm-concordant treatment significantly increased from 84.45% to 86.03% during the year of 2015-2017. Among the patients who received recommended first-line drugs with subsequent optimized treatment (n = 2977), the concordance proportion was 27.24%. Mirtazapine and trazodone were the most used drugs for adjunctive strategy. Inadequate or extended duration before optimized treatment are common inconsistency. The median length of follow-up for algorithm-concordant (n = 811) and algorithm-discordant patients (n = 2166) were 153 days (Q1-Q3 = 79-328) and 368 days (Q1-Q3 = 181-577) respectively, and the average number of clinical visits per person-year was 13.07 and 13.08 respectively. Conclusion: Gap existed between clinical practice and AD algorithm. Improved access to evidence-based treatment is required, especially for optimized strategies during outpatient follow-up.
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Affiliation(s)
- Lu Yang
- Clinical Research Center and Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yousong Su
- Clinical Research Center and Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Sijia Dong
- Global Epidemiology, Office of Chief Medical Officer, Johnson & Johnson, Shanghai, China
| | - Tao Wu
- Global Epidemiology, Office of Chief Medical Officer, Johnson & Johnson, Beijing, China
| | - Yongjing Zhang
- Global Epidemiology, Office of Chief Medical Officer, Johnson & Johnson, Shanghai, China
| | - Hong Qiu
- Global Epidemiology, Office of Chief Medical Officer, Johnson & Johnson, Titusville, NJ, United States
| | - Wenjie Gu
- Clinical Research Center and Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hong Qiu
- Clinical Research Center and Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yifeng Xu
- Clinical Research Center and Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - JianLi Wang
- Departments of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada
| | - Jun Chen
- Clinical Research Center and Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Yiru Fang
- Clinical Research Center and Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
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Arsenault E, Lavigne AA, Mansouri S, Gagné AM, Francis K, Bittar TP, Quessy F, Abdallah K, Barbeau A, Hébert M, Labonté B. Sex-Specific Retinal Anomalies Induced by Chronic Social Defeat Stress in Mice. Front Behav Neurosci 2021; 15:714810. [PMID: 34483859 PMCID: PMC8415161 DOI: 10.3389/fnbeh.2021.714810] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 07/20/2021] [Indexed: 01/04/2023] Open
Abstract
Major depressive disorder (MDD) is one of the most common consequences of chronic stress. Still, there is currently no reliable biomarker to detect individuals at risk to develop the disease. Recently, the retina emerged as an effective way to investigate psychiatric disorders using the electroretinogram (ERG). In this study, cone and rod ERGs were performed in male and female C57BL/6 mice before and after chronic social defeat stress (CSDS). Mice were then divided as susceptible or resilient to stress. Our results suggest that CSDS reduces the amplitude of both oscillatory potentials and a-waves in the rods of resilient but not susceptible males. Similar effects were revealed following the analysis of the cone b-waves, which were faster after CSDS in resilient mice specifically. In females, rod ERGs revealed age-related changes with no change in cone ERGs. Finally, our analysis suggests that baseline ERG can predict with an efficacy up to 71% the expression of susceptibility and resilience before stress exposition in males and females. Overall, our findings suggest that retinal activity is a valid biomarker of stress response that could potentially serve as a tool to predict whether males and females will become susceptible or resilient when facing CSDS.
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Affiliation(s)
- Eric Arsenault
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada.,Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec City, QC, Canada
| | - Andrée-Anne Lavigne
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada
| | - Samaneh Mansouri
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada.,Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC, Canada
| | - Anne-Marie Gagné
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada
| | - Kimberley Francis
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada
| | - Thibault P Bittar
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada.,Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec City, QC, Canada
| | - Francis Quessy
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada.,Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec City, QC, Canada
| | - Khaled Abdallah
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada
| | - Annie Barbeau
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada
| | - Marc Hébert
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada.,Department of Ophthalmology and Otorhinolaryngology-Head and Neck Surgery, Faculty of Medicine, Université Laval, Quebec City, QC, Canada
| | - Benoit Labonté
- CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale Nationale, Quebec City, QC, Canada.,Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec City, QC, Canada
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Carvalho S, Caetano F, Pinto-Gouveia J, Mota-Pereira J, Maia D, Pimentel P, Priscila C, Gilbert P. Predictors of poor 6-week outcome in a cohort of major depressive disorder patients treated with antidepressant medication: the role of entrapment. Nord J Psychiatry 2021; 75:38-48. [PMID: 32646266 DOI: 10.1080/08039488.2020.1790657] [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] [Indexed: 10/23/2022]
Abstract
BACKGROUND Only a small number of consistent processes predict which depressed patients will achieve remission with antidepressant medication. One set of processes is that of social ranking strategies/variables that are related to life events and severe difficulties. Particularly, defeat and entrapment predict poorer response to antidepressants. However, results are inconsistent. AIM The current study aimed to evaluate evolutionary strategies, childhood maltreatment, neglect and life events and difficulties (LEDs) as predictors of remission in depressed patients undergoing pharmacological treatment in a psychiatric outpatient sample. METHODS A cohort of 139 depressed outpatients undergoing pharmacological treatment was followed prospectively in a naturalistic study for 6 weeks. Two major evaluations were considered at baseline and 6 weeks. We allocated patients to a pharmacological treatment algorithm for depression - the Texas Medication Algorithm Project. Variables evaluated at baseline and tested as predictors of remission included demographic and clinical data, severity of depression, social ranking, evolution informed variables, LEDs and childhood maltreatment. RESULTS Of the 139 patients, only 24.5% were remitted at week 6. In univariate analyses, non-remitted patients scored significantly higher in all psychopathology and vulnerability scales except for submissive behaviour and internal entrapment. For the logistic regression, a higher load of LEDs of the entrapment and humiliation dimension in the year before the index episode (OR = 6.62), and higher levels external entrapment in the Entrapment Scale (OR = 1.10) predicted non-remission. These variables accounted for 28.7% of the variance. CONCLUSIONS Multivariate analysis revealed that external entrapment was the only predictor of non-remission.
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Affiliation(s)
| | | | - José Pinto-Gouveia
- CINEICC, Faculdade de Psicologia e Ciências da Educação, Universidade de Coimbra, Portugal
| | | | - Dulce Maia
- Departamento de Psiquiatria e Saúde Mental, Centro Hospitalar de Trás-os-Montes e Alto Douro, Vila Real, Portugal
| | - Paulo Pimentel
- Departamento de Psiquiatria e Saúde Mental, Centro Hospitalar de Trás-os-Montes e Alto Douro, Vila Real, Portugal
| | | | - Paul Gilbert
- Centre for Compassion Research and Training, College of Health and Social Care, University of Derby, Derby, UK
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