1
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Adams MJ, Thorp JG, Jermy BS, Kwong ASF, Kõiv K, Grotzinger AD, Nivard MG, Marshall S, Milaneschi Y, Baune BT, Müller-Myhsok B, Penninx BWJH, Boomsma DI, Levinson DF, Breen G, Pistis G, Grabe HJ, Tiemeier H, Berger K, Rietschel M, Magnusson PK, Uher R, Hamilton SP, Lucae S, Lehto K, Li QS, Byrne EM, Hickie IB, Martin NG, Medland SE, Wray NR, Tucker-Drob EM, Lewis CM, McIntosh AM, Derks EM. Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts. Psychol Med 2024:1-10. [PMID: 39324397 DOI: 10.1017/s0033291724001880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/27/2024]
Abstract
BACKGROUND Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data. METHODS We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors. RESULTS The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms). CONCLUSION The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.
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Affiliation(s)
- Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Jackson G Thorp
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Bradley S Jermy
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Alex S F Kwong
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Kadri Kõiv
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Andrew D Grotzinger
- Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Michel G Nivard
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Sally Marshall
- Centre for Genomic & Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bernhard T Baune
- Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
- Department of Psychiatry, University of Münster, Münster, NRW, Germany
| | - Bertram Müller-Myhsok
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, BY, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, BY, Germany
- Institute of Population Health, University of Liverpool, Liverpool, UK
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology & Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Douglas F Levinson
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, King's College London, London, UK
| | - Giorgio Pistis
- Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, VD, Switzerland
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, MV, Germany
| | - Henning Tiemeier
- Child and Adolescent Psychiatry, Erasmus University Medical Center Rotterdam, Rotterdam, Netherlands
- Social and Behavioral Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, NRW, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, BW, Germany
| | - Patrik K Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Rudolf Uher
- Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Steven P Hamilton
- Psychiatry, Kaiser Permanente Northern California, San Francisco, CA, USA
| | - Susanne Lucae
- Max Planck Institute of Psychiatry, Munich, BY, Germany
| | - Kelli Lehto
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Qingqin S Li
- Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, NJ, USA
| | - Enda M Byrne
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Nicholas G Martin
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sarah E Medland
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Elliot M Tucker-Drob
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
- Department of Medical & Molecular Genetics, King's College London, London, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Institute for Genomics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Eske M Derks
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
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2
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Bertollo AG, Galvan ACL, Dallagnol C, Cortez AD, Ignácio ZM. Early Life Stress and Major Depressive Disorder-An Update on Molecular Mechanisms and Synaptic Impairments. Mol Neurobiol 2024; 61:6469-6483. [PMID: 38307968 DOI: 10.1007/s12035-024-03983-2] [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: 07/05/2023] [Accepted: 01/21/2024] [Indexed: 02/04/2024]
Abstract
Early life stress (ELS), characterized as abuse, neglect, and abandonment, can cause several adverse consequences in the lives of affected individuals. ELS experiences can affect an individual's development in variable ways, persisting in the long term and promoting lasting impacts, considering that early exposure to stressors can be biologically incorporated, as prolonged stimulation of stress response systems affects the development of the brain structure and other body systems, increasing the risk of diseases associated with stress and cognitive impairment. This type of stress increases the risk of developing major depressive disorder (MDD) in a severe form that does not respond adequately to traditional antidepressant treatments. Several alterations are studied as mechanisms that relate ELS with MDD, such as epigenetic alterations, neurotransmitters, and neuronal signaling. This review discusses research that brings evidence about the ELS mechanisms involved in synaptic impairments and MDD. The processes involved in epigenetic changes and the HPA axis are highlighted, as well as changes in neurotransmitters and neuronal signaling mechanisms.
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Affiliation(s)
- Amanda Gollo Bertollo
- Laboratory of Physiology Pharmacology and Psychopathology, Graduate Program in Biomedical Sciences, Federal University of Fronteira Sul, Chapecó, SC, 89815-899, Brazil
| | - Agatha Carina Leite Galvan
- Laboratory of Physiology Pharmacology and Psychopathology, Graduate Program in Biomedical Sciences, Federal University of Fronteira Sul, Chapecó, SC, 89815-899, Brazil
| | - Claudia Dallagnol
- Laboratory of Physiology Pharmacology and Psychopathology, Graduate Program in Biomedical Sciences, Federal University of Fronteira Sul, Chapecó, SC, 89815-899, Brazil
| | - Arthur Dellazeri Cortez
- Laboratory of Physiology Pharmacology and Psychopathology, Graduate Program in Biomedical Sciences, Federal University of Fronteira Sul, Chapecó, SC, 89815-899, Brazil
| | - Zuleide Maria Ignácio
- Laboratory of Physiology Pharmacology and Psychopathology, Graduate Program in Biomedical Sciences, Federal University of Fronteira Sul, Chapecó, SC, 89815-899, Brazil.
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3
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Sanchez-Ruiz JA, Coombes BJ, Pazdernik VM, Melhuish Beaupre LM, Jenkins GD, Pendegraft RS, Batzler A, Ozerdem A, McElroy SL, Gardea-Resendez MA, Cuellar-Barboza AB, Prieto ML, Frye MA, Biernacka JM. Clinical and genetic contributions to medical comorbidity in bipolar disorder: a study using electronic health records-linked biobank data. Mol Psychiatry 2024; 29:2701-2713. [PMID: 38548982 DOI: 10.1038/s41380-024-02530-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 02/21/2024] [Accepted: 03/13/2024] [Indexed: 06/14/2024]
Abstract
Bipolar disorder is a chronic and complex polygenic disease with high rates of comorbidity. However, the independent contribution of either diagnosis or genetic risk of bipolar disorder to the medical comorbidity profile of individuals with the disease remains unresolved. Here, we conducted a multi-step phenome-wide association study (PheWAS) of bipolar disorder using phenomes derived from the electronic health records of participants enrolled in the Mayo Clinic Biobank and the Mayo Clinic Bipolar Disorder Biobank. First, we explored the conditions associated with a diagnosis of bipolar disorder by conducting a phenotype-based PheWAS followed by LASSO-penalized regression to account for correlations within the phenome. Then, we explored the conditions associated with bipolar disorder polygenic risk score (BD-PRS) using a PRS-based PheWAS with a sequential exclusion approach to account for the possibility that diagnosis, instead of genetic risk, may drive such associations. 53,386 participants (58.7% women) with a mean age at analysis of 67.8 years (SD = 15.6) were included. A bipolar disorder diagnosis (n = 1479) was associated with higher rates of psychiatric conditions, injuries and poisonings, endocrine/metabolic and neurological conditions, viral hepatitis C, and asthma. BD-PRS was associated with psychiatric comorbidities but, in contrast, had no positive associations with general medical conditions. While our findings warrant confirmation with longitudinal-prospective studies, the limited associations between bipolar disorder genetics and medical conditions suggest that shared environmental effects or environmental consequences of diagnosis may have a greater impact on the general medical comorbidity profile of individuals with bipolar disorder than its genetic risk.
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Affiliation(s)
| | - Brandon J Coombes
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Greg D Jenkins
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - Anthony Batzler
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Aysegul Ozerdem
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Susan L McElroy
- Lindner Center of HOPE/University of Cincinnati, Cincinnati, OH, USA
| | - Manuel A Gardea-Resendez
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - Alfredo B Cuellar-Barboza
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - Miguel L Prieto
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry, Faculty of Medicine, Universidad de Los Andes, Santiago, Chile
- Mental Health Service, Clínica Universidad de los Andes, Santiago, Chile
| | - Mark A Frye
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Joanna M Biernacka
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA.
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
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4
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Sanchez-Ruiz JA, Treviño-Alvarez AM, Zambrano-Lucio M, Lozano Díaz ST, Wang N, Biernacka JM, Tye SJ, Cuellar-Barboza AB. The Wnt signaling pathway in major depressive disorder: A systematic review of human studies. Psychiatry Res 2024; 339:115983. [PMID: 38870775 DOI: 10.1016/j.psychres.2024.115983] [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: 03/01/2024] [Revised: 05/20/2024] [Accepted: 05/26/2024] [Indexed: 06/15/2024]
Abstract
Despite uncertainty about the specific molecular mechanisms driving major depressive disorder (MDD), the Wnt signaling pathway stands out as a potentially influential factor in the pathogenesis of MDD. Known for its role in intercellular communication, cell proliferation, and fate, Wnt signaling has been implicated in diverse biological phenomena associated with MDD, spanning neurodevelopmental to neurodegenerative processes. In this systematic review, we summarize the functional differences in protein and gene expression of the Wnt signaling pathway, and targeted genetic association studies, to provide an integrated synthesis of available human data examining Wnt signaling in MDD. Thirty-three studies evaluating protein expression (n = 15), gene expression (n = 9), or genetic associations (n = 9) were included. Only fifteen demonstrated a consistently low overall risk of bias in selection, comparability, and exposure. We found conflicting observations of limited and distinct Wnt signaling components across diverse tissue sources. These data do not demonstrate involvement of Wnt signaling dysregulation in MDD. Given the well-established role of Wnt signaling in antidepressant response, we propose that a more targeted and functional assessment of Wnt signaling is needed to understand its role in depression pathophysiology. Future studies should include more components, assess multiple tissues concurrently, and follow a standardized approach.
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Affiliation(s)
- Jorge A Sanchez-Ruiz
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | | | | | - Sofía T Lozano Díaz
- Vicerrectoría de Ciencias de la Salud, Universidad de Monterrey, San Pedro Garza Garcia, Nuevo Leon, Mexico
| | - Ning Wang
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Joanna M Biernacka
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Susannah J Tye
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Department of Psychiatry & Behavioral Sciences, Emory University, Atlanta, GA, USA; Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Alfredo B Cuellar-Barboza
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, Mexico.
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5
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Bonk S, Eszlari N, Kirchner K, Gezsi A, Garvert L, Kuokkanen M, Cano I, Grabe HJ, Antal P, Juhasz G, Van der Auwera S. Impact of gene-by-trauma interaction in MDD-related multimorbidity clusters. J Affect Disord 2024; 359:382-391. [PMID: 38806065 DOI: 10.1016/j.jad.2024.05.126] [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: 09/27/2023] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) is considerably heterogeneous in terms of comorbidities, which may hamper the disentanglement of its biological mechanism. In a previous study, we classified the lifetime trajectories of MDD-related multimorbidities into seven distinct clusters, each characterized by unique genetic and environmental risk-factor profiles. The current objective was to investigate genome-wide gene-by-environment (G × E) interactions with childhood trauma burden, within the context of these clusters. METHODS We analyzed 77,519 participants and 6,266,189 single-nucleotide polymorphisms (SNPs) of the UK Biobank database. Childhood trauma burden was assessed using the Childhood Trauma Screener (CTS). For each cluster, Plink 2.0 was used to calculate SNP × CTS interaction effects on the participants' cluster membership probabilities. We especially focused on the effects of 31 candidate genes and associated SNPs selected from previous G × E studies for childhood maltreatment's association with depression. RESULTS At SNP-level, only the high-multimorbidity Cluster 6 revealed a genome-wide significant SNP rs145772219. At gene-level, MPST and PRH2 were genome-wide significant for the low-multimorbidity Clusters 1 and 3, respectively. Regarding candidate SNPs for G × E interactions, individual SNP results could be replicated for specific clusters. The candidate genes CREB1, DBH, and MTHFR (Cluster 5) as well as TPH1 (Cluster 6) survived multiple testing correction. LIMITATIONS CTS is a short retrospective self-reported measurement. Clusters could be influenced by genetics of individual disorders. CONCLUSIONS The first G × E GWAS for MDD-related multimorbidity trajectories successfully replicated findings from previous G × E studies related to depression, and revealed risk clusters for the contribution of childhood trauma.
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Affiliation(s)
- Sarah Bonk
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Nora Eszlari
- Department of Pharmacodynamics, Faculty of Pharmaceutical Sciences, Semmelweis University, Nagyvárad tér 4., H-1089 Budapest, Hungary; NAP3.0-SE Neuropsychopharmacology Research Group, Hungarian Brain Research Program, Semmelweis University, Üllői út 26., H-1085 Budapest, Hungary
| | - Kevin Kirchner
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Andras Gezsi
- Department of Measurement and Information Systems, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Linda Garvert
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Mikko Kuokkanen
- Department of Public Health and Welfare, Finnish Health and Welfare Institute. Biomedicum 1, Haartmaninkatu 8, 00290 Helsinki, Finland; Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine at University of Texas Rio Grande Valley, Brownsville, TX, United States; Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Finland
| | - Isaac Cano
- Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Villarroel 170, Barcelona 08036. Spain
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; German Centre for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Greifswald, Germany
| | - Peter Antal
- Department of Measurement and Information Systems, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Gabriella Juhasz
- Department of Pharmacodynamics, Faculty of Pharmaceutical Sciences, Semmelweis University, Nagyvárad tér 4., H-1089 Budapest, Hungary; NAP3.0-SE Neuropsychopharmacology Research Group, Hungarian Brain Research Program, Semmelweis University, Üllői út 26., H-1085 Budapest, Hungary
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; German Centre for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Greifswald, Germany.
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6
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Aouci R, Fontaine A, Vion A, Belz L, Levi G, Narboux-Nême N. The Antidepressant Action of Fluoxetine Involves the Inhibition of Dlx5/6 in Cortical GABAergic Neurons through a TrkB-Dependent Pathway. Cells 2024; 13:1262. [PMID: 39120293 PMCID: PMC11311550 DOI: 10.3390/cells13151262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2024] [Revised: 07/17/2024] [Accepted: 07/24/2024] [Indexed: 08/10/2024] Open
Abstract
Major depressive disorder (MDD) is a complex and devastating illness that affects people of all ages. Despite the large use of antidepressants in current medical practice, neither their mechanisms of action nor the aetiology of MDD are completely understood. Experimental evidence supports the involvement of Parvalbumin-positive GABAergic neurons (PV-neurons) in the pathogenesis of MDD. DLX5 and DLX6 (DLX5/6) encode two homeodomain transcription factors involved in cortical GABAergic differentiation and function. In the mouse, the level of expression of these genes is correlated with the cortical density of PV-neurons and with anxiety-like behaviours. The same genomic region generates the lncRNA DLX6-AS1, which, in humans, participates in the GABAergic regulatory module downregulated in schizophrenia and ASD. Here, we show that the expression levels of Dlx5/6 in the adult mouse brain are correlated with the immobility time in the forced swim test, which is used to measure depressive-like behaviours. We show that the administration of the antidepressant fluoxetine (Flx) to normal mice induces, within 24 h, a rapid and stable reduction in Dlx5, Dlx6 and Dlx6-AS1 expression in the cerebral cortex through the activation of the TrkB-CREB pathway. Experimental Dlx5 overexpression counteracts the antidepressant effects induced by Flx treatment. Our findings show that one of the short-term effects of Flx administration is the reduction in Dlx5/6 expression in GABAergic neurons, which, in turn, has direct consequences on PV expression and on behavioural profiles. Variants in the DLX5/6 regulatory network could be implicated in the predisposition to depression and in the variability of patients' response to antidepressant treatment.
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Affiliation(s)
| | | | | | | | | | - Nicolas Narboux-Nême
- Molecular Physiology and Adaption, UMR7221 CNRS, Museum National d’Histoire Naturelle, 75005 Paris, France; (R.A.); (A.F.); (L.B.); (G.L.)
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7
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Strom NI, Verhulst B, Bacanu SA, Cheesman R, Purves KL, Gedik H, Mitchell BL, Kwong AS, Faucon AB, Singh K, Medland S, Colodro-Conde L, Krebs K, Hoffmann P, Herms S, Gehlen J, Ripke S, Awasthi S, Palviainen T, Tasanko EM, Peterson RE, Adkins DE, Shabalin AA, Adams MJ, Iveson MH, Campbell A, Thomas LF, Winsvold BS, Drange OK, Børte S, Ter Kuile AR, Nguyen TH, Meier SM, Corfield EC, Hannigan L, Levey DF, Czamara D, Weber H, Choi KW, Pistis G, Couvy-Duchesne B, Van der Auwera S, Teumer A, Karlsson R, Garcia-Argibay M, Lee D, Wang R, Bjerkeset O, Stordal E, Bäckmann J, Salum GA, Zai CC, Kennedy JL, Zai G, Tiwari AK, Heilmann-Heimbach S, Schmidt B, Kaprio J, Kennedy MM, Boden J, Havdahl A, Middeldorp CM, Lopes FL, Akula N, McMahon FJ, Binder EB, Fehm L, Ströhle A, Castelao E, Tiemeier H, Stein DJ, Whiteman D, Olsen C, Fuller Z, Wang X, Wray NR, Byrne EM, Lewis G, Timpson NJ, Davis LK, Hickie IB, Gillespie NA, Milani L, Schumacher J, Woldbye DP, Forstner AJ, Nöthen MM, Hovatta I, Horwood J, Copeland WE, Maes HH, McIntosh AM, Andreassen OA, Zwart JA, Mors O, Børglum AD, Mortensen PB, Ask H, Reichborn-Kjennerud T, Najman JM, Stein MB, Gelernter J, Milaneschi Y, Penninx BW, Boomsma DI, Maron E, Erhardt-Lehmann A, Rück C, Kircher TT, Melzig CA, Alpers GW, Arolt V, Domschke K, Smoller JW, Preisig M, Martin NG, Lupton MK, Luik AI, Reif A, Grabe HJ, Larsson H, Magnusson PK, Oldehinkel AJ, Hartman CA, Breen G, Docherty AR, Coon H, Conrad R, Lehto K, Deckert J, Eley TC, Mattheisen M, Hettema JM. Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.03.24309466. [PMID: 39006447 PMCID: PMC11245051 DOI: 10.1101/2024.07.03.24309466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder, and phobias) are highly prevalent, often onset early, persist throughout life, and cause substantial global disability. Although distinct in their clinical presentations, they likely represent differential expressions of a dysregulated threat-response system. Here we present a genome-wide association meta-analysis comprising 122,341 European ancestry ANX cases and 729,881 controls. We identified 58 independent genome-wide significant ANX risk variants and 66 genes with robust biological support. In an independent sample of 1,175,012 self-report ANX cases and 1,956,379 controls, 51 of the 58 associated variants were replicated. As predicted by twin studies, we found substantial genetic correlation between ANX and depression, neuroticism, and other internalizing phenotypes. Follow-up analyses demonstrated enrichment in all major brain regions and highlighted GABAergic signaling as one potential mechanism underlying ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies.
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Affiliation(s)
- Nora I Strom
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Brad Verhulst
- Psychiatry and Behavioral Sciences, Texas A&M University, College Station, Texas, USA
| | | | - Rosa Cheesman
- PROMENTA Centre, Department of Psychology, University of Oslo, Oslo, Norway
| | - Kirstin L Purves
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Hüseyin Gedik
- Institute for Genomics in Health, Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Health Sciences University, Brooklyn, New York, USA
- Life Sciences, Integrative Life Sciences Doctoral Program, Virginia Commonwealth University, Richmond, Virginia, USA
- Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Brittany L Mitchell
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, Queensland University , Brisbane, Queensland, Australia
| | - Alex S Kwong
- Bristol Medical School, Population Health Sciences, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Centre for Clinical Brain Sciences, Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Annika B Faucon
- Division of Medicine, Human Genetics, Vanderbilt University, Nashville, Tennessee, USA
| | - Kritika Singh
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sarah Medland
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Lucia Colodro-Conde
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Psychology, The University of Queensland, Brisbane, Queensland, Australia
| | - Kristi Krebs
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Department of Biomedicine, Human Genomics Research Group, University of Basel; University Hospital Basel, Basel, Switzerland
| | - Stefan Herms
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Medical Genetics and Pathology, Medical Faculty, University Hospital Basel, Basel, Switzerland
- Department of Biomedicine, Human Genomics Research Group, University of Basel; University Hospital Basel, Basel, Switzerland
| | - Jan Gehlen
- Center for Human Genetics, University of Marburg, Marburg, Germany
| | - Stephan Ripke
- Dept. of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Swapnil Awasthi
- Dept. of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Teemu Palviainen
- Helsinki Institute of Life Science, Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Elisa M Tasanko
- Faculty of Medicine, Department of Psychology and Logopedics, SleepWell Research Program, University of Helsinki, Helsinki, Finland
| | - Roseann E Peterson
- Institute for Genomics in Health, Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Health Sciences University, Brooklyn, New York, USA
- Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Daniel E Adkins
- School of Medicine, Department of Psychiatry, University of Utah, Salt Lake City, Utah, USA
| | - Andrey A Shabalin
- School of Medicine, Department of Psychiatry, University of Utah, Salt Lake City, Utah, USA
| | - Mark J Adams
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Matthew H Iveson
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- College of Medicine and Veterinary Medicine, Institute of Genetics and Cancer; Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Laurent F Thomas
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Bendik S Winsvold
- Division of Clinical Neuroscience, Department of Research and Innovation, Oslo University Hospital, Oslo, Norway
- Department of Public Health and Nursing, HUNT Center for Molecular and Clinical Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Ole Kristian Drange
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
- Division of Mental Health, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- NORMENT Centre, University of Oslo, Oslo, Norway
- Centre of Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Psychiatry, Sørlandet Hospital, Kristiansand, Norway
| | - Sigrid Børte
- Division of Clinical Neuroscience, Department of Research and Innovation; Musculoskeletal Health, Oslo University Hospital, Oslo, Norway
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Public Health and Nursing, HUNT Center for Molecular and Clinical Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Abigail R Ter Kuile
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK
- Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom
| | - Tan-Hoang Nguyen
- Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Sandra M Meier
- Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Elizabeth C Corfield
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute , Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Laurie Hannigan
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Daniel F Levey
- Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, New Haven, Connecticut, USA
- Psychiatry, Research, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Darina Czamara
- Department of Genes and Environment, Max-Planck Institute of Psychiatry, Munich, Germany
| | - Heike Weber
- Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, Würzburg, Germany
| | - Karmel W Choi
- Psychiatry, Center for Precision Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
- Psychiatry, Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Giorgio Pistis
- Psychiatric Epidemiology and Psychopathology Research Center, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Baptiste Couvy-Duchesne
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- ARAMIS laboratory, Paris Brain Institute, Paris, France
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Miguel Garcia-Argibay
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Donghyung Lee
- Department of Statistics, Miami University, Oxford, Ohio, USA
| | - Rujia Wang
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ottar Bjerkeset
- Faculty of Nursing and Health Science, Nord University, Levanger, Norway
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Eystein Stordal
- Department of Psychiatry, Hospital Namsos, Nord-Trøndelag Health Trustt, Namsos, Norway
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Julia Bäckmann
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Giovanni A Salum
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Child Psychiatry, National Institute of Developmental Psychiatry, São Paulo, Brazil
| | - Clement C Zai
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Sciences Department, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Division of Neurosciences and Clinical Translation, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - James L Kennedy
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Sciences Department, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Division of Neurosciences and Clinical Translation, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Gwyneth Zai
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Sciences Department, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Division of Neurosciences and Clinical Translation, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Arun K Tiwari
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Sciences Department, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Division of Neurosciences and Clinical Translation, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Jaakko Kaprio
- Helsinki Institute of Life Science, Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Martin M Kennedy
- Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Joseph Boden
- Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - Alexandra Havdahl
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- PROMENTA Centre, Department of Psychology, University of Oslo, Oslo, Norway
- Bristol Medical School, Population Health Sciences, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Christel M Middeldorp
- Child Health Research Centre, University of Queensland, Brisbane, Queensland, Australia
- Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, Queensland, Australia
| | - Fabiana L Lopes
- National Institute of Mental Health, Human Genetics Branch, National Institutes of Health, Bethesda, Maryland, USA
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Nirmala Akula
- National Institute of Mental Health, Genetic Basis of Mood and Anxiety Disorders, National Institutes of Health, Bethesda, Maryland, USA
| | - Francis J McMahon
- National Institute of Mental Health, Genetic Basis of Mood and Anxiety Disorders, National Institutes of Health, Bethesda, Maryland, USA
- Psychiatry & Behavioral Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Elisabeth B Binder
- Department of Genes and Environment, Max-Planck Institute of Psychiatry, Munich, Germany
| | - Lydia Fehm
- Department of Psychology, Zentrum für Psychotherapie, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Andreas Ströhle
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Enrique Castelao
- Psychiatric Epidemiology and Psychopathology Research Center, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Henning Tiemeier
- Social and Behavioral Science, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
- Child and Adolescent Psychiatry, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Dan J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - David Whiteman
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Catherine Olsen
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | | | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Enda M Byrne
- Child Health Research Centre, University of Queensland, Brisbane, Queensland, Australia
| | - Glyn Lewis
- UCL Division of Psychiatry, University College London, London, UK
| | - Nicholas J Timpson
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Lea K Davis
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | | | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - David P Woldbye
- Department of Neuroscience, Laboratory of Neural Plasticity, University of Copenhagen, Copenhagen, Denmark
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Center for Human Genetics, University of Marburg, Marburg, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Iiris Hovatta
- Faculty of Medicine, Department of Psychology and Logopedics and SleepWell Research Program, University of Helsinki, Helsinki, Finland
| | - John Horwood
- Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - William E Copeland
- UVM Medical Center, Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Hermine H Maes
- Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
- Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
- Massey Cancer Center, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Andrew M McIntosh
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Centre of Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- K. G. Jebsen Center for Neurodevelopmental disorders, University of Oslo, Oslo, Norway
| | - John-Anker Zwart
- Division of Clinical Neuroscience, Department of Research and Innovation; Musculoskeletal Health, Oslo University Hospital, Oslo, Norway
- Department of Public Health and Nursing, HUNT Center for Molecular and Clinical Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole Mors
- Department of Psychiatry, Psychosis Research Unit, Aarhus University Hospital, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalised Medicine, Aarhus University, Aarhus, Denmark
| | - Preben B Mortensen
- The National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
| | - Helga Ask
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA Centre, Department of Psychology, University of Oslo, Oslo, Norway
| | - Ted Reichborn-Kjennerud
- PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- NORMENT Centre, University of Oslo, Oslo, Norway
| | - Jackob M Najman
- Faculty of Medicine, School of Public Health, University of Queensland, Herston, Queensland, Australia
| | - Murray B Stein
- Psychiatry, University of California San Diego, La Jolla, CA, USA
- School of Public Health, University of California San Diego, La Jolla, CA, USA
| | - Joel Gelernter
- Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, New Haven, Connecticut, USA
- Psychiatry Research, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Departments of Genetics and Neuroscience, Yale University of Medicine, New Haven, Connecticut, USA
| | - Yuri Milaneschi
- Amsterdam Neuroscience; Amsterdam Public Health, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Brenda W Penninx
- Amsterdam Neuroscience; Amsterdam Public Health, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Twin Register and Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Amsterdam Public Health, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Eduard Maron
- Psychiatry, University of Tartu, Tartu, Estonia
- Department of Medicine, Centre for Neuropsychopharmacology,, Division of Brain Sciences, Imperial College London, London, UK
| | - Angelika Erhardt-Lehmann
- Department of Genes and Environment, Max-Planck Institute of Psychiatry, Munich, Germany
- Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
| | - Christian Rück
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Tilo T Kircher
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Christiane A Melzig
- Psychology, Clinical Psychology, Experimental Psychopathology and Psychotherapy, University of Marburg, Marburg, Germany
- Psychology, Biological and Clinical Psychology, University of Greifswald, Greifswald, Germany
| | - Georg W Alpers
- School of Social Sciences, Department of Psychology, University of Mannheim, Mannheim, Germany
| | - Volker Arolt
- Department of Mental Health, Institute for Translational Psychiatry, University of Muenster, Muenster, Germany
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Center for Mental Health (DZPG), Partner Site Berlin, Berlin, Germany
| | - Jordan W Smoller
- Psychiatry, Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Psychiatry, Center for Precision Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Martin Preisig
- Psychiatric Epidemiology and Psychopathology Research Center, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Nicholas G Martin
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Michelle K Lupton
- Brain and Mental Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, Queensland University , Brisbane, Queensland, Australia
- Faculty of Health, Queensland University of technology, Queensland, Australia
| | - Annemarie I Luik
- Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt - Goethe University, Frankfurt, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Henrik Larsson
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik K Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Albertine J Oldehinkel
- Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Catharina A Hartman
- Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Anna R Docherty
- School of Medicine, Psychiatry, University of Utah, Salt Lake City, Utah, USA
- School of Medicine, Psychiatry; Huntsman Mental Health Institute, University of Utah, Salt Lake City, Utah, USA
- Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Hilary Coon
- School of Medicine, Psychiatry, University of Utah, Salt Lake City, Utah, USA
| | - Rupert Conrad
- Department of Psychosomatic Medicine and Psychotherapy, University Hospital Münster, Münster, Germany
| | - Kelli Lehto
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jürgen Deckert
- Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
| | - Thalia C Eley
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Manuel Mattheisen
- Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
- Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - John M Hettema
- Psychiatry and Behavioral Sciences, Texas A&M University, Bryan, Texas, USA
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Polimanti R. Using Medical Records to Investigate the Genetics of Treatment-Resistant Depression Across Health Care Systems. Am J Psychiatry 2024; 181:569-571. [PMID: 38946279 DOI: 10.1176/appi.ajp.20240377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Affiliation(s)
- Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, Department of Chronic Disease Epidemiology, Yale School of Public Health, and Wu Tsai Institute, Yale University, New Haven, Conn.; VA Connecticut Healthcare Center, West Haven
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9
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Chang L, Wang T, Qu Y, Fan X, Zhou X, Wei Y, Hashimoto K. Identification of novel endoplasmic reticulum-related genes and their association with immune cell infiltration in major depressive disorder. J Affect Disord 2024; 356:190-203. [PMID: 38604455 DOI: 10.1016/j.jad.2024.04.029] [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: 12/26/2023] [Revised: 03/25/2024] [Accepted: 04/08/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Several lines of evidence point to an interaction between genetic predisposition and environmental factors in the onset of major depressive disorder (MDD). This study is aimed to investigate the pathogenesis of MDD by identifying key biomarkers, associated immune infiltration using bioinformatic analysis and human postmortem sample. METHODS The Gene Expression Omnibus (GEO) database of GSE98793 was adopted to identify hub genes linked to endoplasmic reticulum (ER) stress-related genes (ERGs) in MDD. Another GEO database of GSE76826 was employed to validate the novel target associated with ERGs and immune infiltration in MDD. Moreover, human postmortem sample from MDD patients was utilized to confirm the differential expression analysis of hub genes. RESULTS We discovered 12 ER stress-related differentially expressed genes (ERDEGs). A LASSO Cox regression analysis helped construct a diagnostic model for these ERDEGs, incorporating immune infiltration analysis revealed that three hub genes (ERLIN1, SEC61B, and USP13) show the significant and consistent expression differences between the two groups. Western blot analysis of postmortem brain samples indicated notably higher expression levels of ERLIN1 and SEC61B in the MDD group, with USP13 also tending to increase compared to control group. LIMITATIONS The utilization of the MDD gene chip in this analysis was sourced from the GEO database, which possesses a restricted number of pertinent gene chip samples. CONCLUSIONS These findings indicate that ERDEGs especially including ERLIN1, SEC61B, and USP13 associated the infiltration of immune cells may be potential diagnostic indicators for MDD.
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Affiliation(s)
- Lijia Chang
- Division of Clinical Neuroscience, Chiba University Center for Forensic Mental Health, Chiba 260-8670, Japan
| | - Tong Wang
- Key Laboratory of Medical Electrophysiology of Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease, Institute of Cardiovascular Research, Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Youge Qu
- Division of Clinical Neuroscience, Chiba University Center for Forensic Mental Health, Chiba 260-8670, Japan
| | - Xinrong Fan
- Department of Cardiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan 646000, China
| | - Xiangyu Zhou
- Basic Medicine Research Innovation Center for Cardiometabolic Diseases, Ministry of Education, Southwest Medical University, Luzhou 646000, China; Department of Thyroid and Vascular Surgery, The Affiliated Hospital, Southwest Medical University, Luzhou 646000, China
| | - Yan Wei
- Key Laboratory of Medical Electrophysiology of Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease, Institute of Cardiovascular Research, Southwest Medical University, Luzhou 646000, Sichuan, China.
| | - Kenji Hashimoto
- Division of Clinical Neuroscience, Chiba University Center for Forensic Mental Health, Chiba 260-8670, Japan.
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10
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Peña JE, Corbett BF, Tamminga CA, Bhatnagar S, Hitti FL. Investigating Resistance to Antidepressants in Animal Models. Neuroscience 2024; 548:69-80. [PMID: 38697464 DOI: 10.1016/j.neuroscience.2024.04.013] [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: 02/07/2024] [Revised: 04/12/2024] [Accepted: 04/25/2024] [Indexed: 05/05/2024]
Abstract
Major depressive disorder is one of the most prevalent psychiatric diseases, and up to 30-40% of patients remain symptomatic despite treatment. Novel therapies are sorely needed, and animal models may be used to elucidate fundamental neurobiological processes that contribute to human disease states. We conducted a systematic review of current preclinical approaches to investigating treatment resistance with the goal of describing a path forward for improving our understanding of treatment resistant depression. We conducted a broad literature search to identify studies relevant to the preclinical investigation of treatment resistant depression. We followed PRISMA (Preferred Reporting Items for Systemic Reviews and Meta-Analyses) guidelines and included all relevant studies. We identified 467 studies in our initial search. Of these studies, we included 69 in our systematic review after applying our inclusion/exclusion criteria. We identified 10 broad strategies for investigating treatment resistance in animal models. Stress hormone administration was the most commonly used model, and the most common behavioral test was the forced swim test. We systematically identified and reviewed current approaches for gaining insight into the neurobiology underlying treatment resistant depression using animal models. Each approach has its advantages and disadvantages, but all require careful consideration of their potential limitations regarding therapeutic translation. An enhanced understanding of treatment resistant depression is sorely needed given the burden of disease and lack of effective therapies.
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Affiliation(s)
- Julianna E Peña
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, United States; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Brian F Corbett
- Department of Biology, Rutgers University, Camden, NJ, United States
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Seema Bhatnagar
- Department of Anesthesiology and Critical Care, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, United States
| | - Frederick L Hitti
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, United States; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States.
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11
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Dahrendorff J, Currier G, Uddin M. Leveraging DNA methylation to predict treatment response in major depressive disorder: A critical review. Am J Med Genet B Neuropsychiatr Genet 2024:e32985. [PMID: 38650309 DOI: 10.1002/ajmg.b.32985] [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: 09/26/2023] [Revised: 03/18/2024] [Accepted: 04/02/2024] [Indexed: 04/25/2024]
Abstract
Major depressive disorder (MDD) is a debilitating and prevalent mental disorder with a high disease burden. Despite a wide array of different treatment options, many patients do not respond to initial treatment attempts. Selection of the most appropriate treatment remains a significant clinical challenge in psychiatry, highlighting the need for the development of biomarkers with predictive utility. Recently, the epigenetic modification DNA methylation (DNAm) has emerged to be of great interest as a potential predictor of MDD treatment outcomes. Here, we review efforts to date that seek to identify DNAm signatures associated with treatment response in individuals with MDD. Searches were conducted in the databases PubMed, Scopus, and Web of Science with the concepts and keywords MDD, DNAm, antidepressants, psychotherapy, cognitive behavior therapy, electroconvulsive therapy, transcranial magnetic stimulation, and brain stimulation therapies. We identified 32 studies implicating DNAm patterns associated with MDD treatment outcomes. The majority of studies (N = 25) are focused on selected target genes exploring treatment outcomes in pharmacological treatments (N = 22) with a few studies assessing treatment response to electroconvulsive therapy (N = 3). Additionally, there are few genome-scale efforts (N = 7) to characterize DNAm patterns associated with treatment outcomes. There is a relative dearth of studies investigating DNAm patterns in relation to psychotherapy, electroconvulsive therapy, or transcranial magnetic stimulation; importantly, most existing studies have limited sample sizes. Given the heterogeneity in both methods and results of studies to date, there is a need for additional studies before existing findings can inform clinical decisions.
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Affiliation(s)
- Jan Dahrendorff
- Genomics Program, College of Public Health, University of South Florida, Tampa, Florida, USA
| | - Glenn Currier
- Department of Psychiatry and Behavioral Neurosciences, University of South Florida, Tampa, Florida, USA
| | - Monica Uddin
- Genomics Program, College of Public Health, University of South Florida, Tampa, Florida, USA
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12
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Liu X, Wu Y, Li M. Identification of 7 mitochondria-related genes as diagnostic biomarkers of MDD and their correlation with immune infiltration: New insights from bioinformatics analysis. J Affect Disord 2024; 349:86-100. [PMID: 38199392 DOI: 10.1016/j.jad.2024.01.011] [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: 04/18/2023] [Revised: 11/23/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) is one of the most prevalent and debilitating psychiatric disorders. It becomes more recognized that mitochondrial dysfunction contributes to the pathophysiology of depression. However, little research has systematically investigated the mitochondria-related biomarkers for MDD diagnosis. This study aimed to develop a novel diagnostic gene signature in MDD based on mitochondria-related genes. METHOD We identified the differentially expressed mitochondrial-related genes (DeMRGs) by combing the gene expression data of the GEO database with mitochondria-related gene lists obtained from the MitoCarta3.0 database. Next, three kinds of machine-learning algorithms were used to screen characteristic DeMRGs. Then, we constructed a multivariable diagnostic model based on these characteristic genes and evaluated the diagnostic ability of this model. Subsequently, the immune landscape of infiltrated immune cells between MDD patients and controls was evaluated by CIBERSORT. Using consensus clustering analysis, we divided MDD patients into different clusters based on the characteristic DeMRGs expression patterns. Finally, the variations in immune cell infiltration between different clusters, and the correlation between characteristic DeMRGs and immune cell infiltration were analyzed. RESULTS Seven characteristic genes, including PMPCB, MRPS28, LYRM2, MGST1, COX20, PTPMT1, and STX17, were identified from the 31 DeMRGs. Based on the seven characteristic genes, we successfully constructed a diagnostic model which had relatively good diagnostic performance and potential application in the clinical diagnosis of MDD. In addition, our results also imply an intimate and comprehensive association between the characteristic DeMRGs and immune infiltrating cells. CONCLUSION A novel mitochondria-related gene signature with a good diagnostic performance and a relationship with immune microenvironment were identified in major depressive disorder.
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Affiliation(s)
- Xiaolan Liu
- Psychiatric Intensive Care Unit (PICU), Wuhan Mental Health Center, Wuhan 430012, Hubei Province, China; Department of Depression, Wuhan Hospital for Psychotherapy, Wuhan 430012, Hubei Province, China.
| | - Yong Wu
- Psychiatric Intensive Care Unit (PICU), Wuhan Mental Health Center, Wuhan 430012, Hubei Province, China; Department of Depression, Wuhan Hospital for Psychotherapy, Wuhan 430012, Hubei Province, China
| | - Mingxing Li
- Psychiatric Intensive Care Unit (PICU), Wuhan Mental Health Center, Wuhan 430012, Hubei Province, China; Department of Depression, Wuhan Hospital for Psychotherapy, Wuhan 430012, Hubei Province, China.
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13
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Oh EY, Han KM, Kim A, Kang Y, Tae WS, Han MR, Ham BJ. Integration of whole-exome sequencing and structural neuroimaging analysis in major depressive disorder: a joint study. Transl Psychiatry 2024; 14:141. [PMID: 38461185 PMCID: PMC10924915 DOI: 10.1038/s41398-024-02849-4] [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: 09/15/2023] [Revised: 02/07/2024] [Accepted: 02/22/2024] [Indexed: 03/11/2024] Open
Abstract
Major depressive disorder (MDD) is a common mental illness worldwide and is triggered by an intricate interplay between environmental and genetic factors. Although there are several studies on common variants in MDD, studies on rare variants are relatively limited. In addition, few studies have examined the genetic contributions to neurostructural alterations in MDD using whole-exome sequencing (WES). We performed WES in 367 patients with MDD and 161 healthy controls (HCs) to detect germline and copy number variations in the Korean population. Gene-based rare variants were analyzed to investigate the association between the genes and individuals, followed by neuroimaging-genetic analysis to explore the neural mechanisms underlying the genetic impact in 234 patients with MDD and 135 HCs using diffusion tensor imaging data. We identified 40 MDD-related genes and observed 95 recurrent regions of copy number variations. We also discovered a novel gene, FRMPD3, carrying rare variants that influence MDD. In addition, the single nucleotide polymorphism rs771995197 in the MUC6 gene was significantly associated with the integrity of widespread white matter tracts. Moreover, we identified 918 rare exonic missense variants in genes associated with MDD susceptibility. We postulate that rare variants of FRMPD3 may contribute significantly to MDD, with a mild penetration effect.
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Affiliation(s)
- Eun-Young Oh
- Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, Republic of Korea
| | - Kyu-Man Han
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
- Brain Convergence Research Center, Korea University College of Medicine, Seoul, Republic of Korea
| | - Aram Kim
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Youbin Kang
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Woo-Suk Tae
- Brain Convergence Research Center, Korea University College of Medicine, Seoul, Republic of Korea
| | - Mi-Ryung Han
- Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, Republic of Korea.
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
- Brain Convergence Research Center, Korea University College of Medicine, Seoul, Republic of Korea.
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14
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Farinha-Ferreira M, Magalhães DM, Neuparth-Sottomayor M, Rafael H, Miranda-Lourenço C, Sebastião AM. Unmoving and uninflamed: Characterizing neuroinflammatory dysfunction in the Wistar-Kyoto rat model of depression. J Neurochem 2024. [PMID: 38430009 DOI: 10.1111/jnc.16083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 01/30/2024] [Accepted: 02/05/2024] [Indexed: 03/03/2024]
Abstract
Reductionistic research on depressive disorders has been hampered by the limitations of animal models. Recently, it has been hypothesized that neuroinflammation is a key player in depressive disorders. The Wistar-Kyoto (WKY) rat is an often-used animal model of depression, but no information so far exists on its neuroinflammatory profile. As such, we compared male young adult WKY rats to Wistar (WS) controls, with regard to both behavioral performance and brain levels of key neuroinflammatory markers. We first assessed anxiety- and depression-like behaviors in a battery consisting of the Elevated Plus Maze (EPM), the Novelty Suppressed Feeding (NSFT), Open Field (OFT), Social Interaction (SIT), Forced Swim (FST), Sucrose Preference (SPT), and Splash tests (ST). We found that WKY rats displayed increased NSFT feeding latency, decreased OFT center zone permanence, decreased EPM open arm permanence, decreased SIT interaction time, and increased immobility in the FST. However, WKY rats also evidenced marked hypolocomotion, which is likely to confound performance in such tests. Interestingly, WKY rats performed similarly, or even above, to WS levels in the SPT and ST, in which altered locomotion is not a significant confound. In a separate cohort, we assessed prefrontal cortex (PFC), hippocampus and amygdala levels of markers of astrocytic (GFAP, S100A10) and microglial (Iba1, CD86, Ym1) activation status, as well as of three key proinflammatory cytokines (IL-1β, IL-6, TNF-α). There were no significant differences between strains in any of these markers, in any of the regions assessed. Overall, results highlight that behavioral data obtained with WKY rats as a model of depression must be carefully interpreted, considering the marked locomotor activity deficits displayed. Furthermore, our data suggest that, despite WKY rats replicating many depression-associated neurobiological alterations, as shown by others, this is not the case for neuroinflammation-related alterations, thus representing a novel limitation of this model.
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Affiliation(s)
- Miguel Farinha-Ferreira
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Daniela M Magalhães
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Mariana Neuparth-Sottomayor
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Hugo Rafael
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Catarina Miranda-Lourenço
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Ana M Sebastião
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
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15
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Shimamoto M, Ishizuka K, Ohtani K, Inada T, Yamamoto M, Tachibana M, Kimura H, Sakai Y, Kobayashi K, Ozaki N, Ikeda M. Machine learning algorithm-based estimation model for the severity of depression assessed using Montgomery-Asberg depression rating scale. Neuropsychopharmacol Rep 2024; 44:115-120. [PMID: 38115795 PMCID: PMC10932776 DOI: 10.1002/npr2.12404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/08/2023] [Accepted: 11/10/2023] [Indexed: 12/21/2023] Open
Abstract
AIM Depressive disorder is often evaluated using established rating scales. However, consistent data collection with these scales requires trained professionals. In the present study, the "rater & estimation-system" reliability was assessed between consensus evaluation by trained psychiatrists and the estimation by 2 models of the AI-MADRS (Montgomery-Asberg Depression Rating Scale) estimation system, a machine learning algorithm-based model developed to assess the severity of depression. METHODS During interviews with trained psychiatrists and the AI-MADRS estimation system, patients responded orally to machine-generated voice prompts from the AI-MADRS structured interview questions. The severity scores estimated from two models of the AI-MADRS estimation system, the max estimation model and the average estimation model, were compared with those by trained psychiatrists. RESULTS A total of 51 evaluation interviews conducted on 30 patients were analyzed. Pearson's correlation coefficient with the scores evaluated by trained psychiatrists was 0.76 (95% confidence interval 0.62-0.86) for the max estimation model, and 0.86 (0.76-0.92) for the average estimation model. The ANOVA ICC rater & estimation-system reliability with the evaluation scores by trained psychiatrists was 0.51 (-0.09 to 0.79) for the max estimation model, and 0.75 (0.55-0.86) for the average estimation model. CONCLUSION The average estimation model of AI-MADRS demonstrated substantially acceptable rater & estimation-system reliability with trained psychiatrists. Accumulating a broader training dataset and the refinement of AI-MADRS interviews are expected to improve the performance of AI-MADRS. Our findings suggest that AI technologies can significantly modernize and potentially revolutionize the realm of depression assessments.
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Affiliation(s)
- Masanori Shimamoto
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaJapan
| | - Kanako Ishizuka
- Health Support CenterNagoya Institute of TechnologyNagoyaJapan
| | - Kento Ohtani
- Department of Intelligent SystemsNagoya University Graduate School of InformaticsNagoyaJapan
| | - Toshiya Inada
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaJapan
| | - Maeri Yamamoto
- Department of PsychiatryNagoya University HospitalNagoyaJapan
| | | | - Hiroki Kimura
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaJapan
| | | | | | - Norio Ozaki
- Pathophysiology of Mental DisordersNagoya University Graduate School of MedicineNagoyaJapan
| | - Masashi Ikeda
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaJapan
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16
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Garcia-Argibay M, Brikell I, Thapar A, Lichtenstein P, Lundström S, Demontis D, Larsson H. Attention-Deficit/Hyperactivity Disorder and Major Depressive Disorder: Evidence From Multiple Genetically Informed Designs. Biol Psychiatry 2024; 95:444-452. [PMID: 37562520 DOI: 10.1016/j.biopsych.2023.07.017] [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: 03/20/2023] [Revised: 07/19/2023] [Accepted: 07/30/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) and major depressive disorder (MDD) are two highly prevalent disorders that frequently co-occur. Prior evidence from genetic and cohort studies supports an association between ADHD and MDD. However, the direction and mechanisms underlying their association remain unclear. As onset of ADHD occurs in early life, it has been hypothesized that ADHD may cause MDD. METHODS We examined the association of ADHD with MDD using 3 different genetically informed methods to disentangle causality from confounding: 1) a nationwide longitudinal register-based full sibling comparison (N = 1,018,489) adjusting for shared familial confounding; 2) a prospective co-twin control study comprising 16,477 twins (5084 monozygotic and 11,393 dizygotic); and 3) a two-sample Mendelian randomization analysis using the largest available ADHD (N = 225,534) and MDD (N = 500,199) genome-wide association study summary statistics, adjusting for correlated and uncorrelated horizontal pleiotropy. RESULTS Sibling and twin comparisons indicated that individuals with ADHD have an increased risk for subsequent development of MDD (hazard ratio = 4.12 [95% CI 3.62-4.69]) after adjusting for shared genetic and familial factors and that ADHD scores endorsed by parents are positively associated with subsequent MDD scores at ages 15 and 18 years (b = 0.07 [95% CI 0.05-0.08] and b = 0.09 [95% CI 0.08-0.11], respectively). Mendelian randomization analyses showed that genetic liability for ADHD is causally related to MDD (odds ratio = 1.15 [95% CI 1.08-1.23]). CONCLUSIONS Our study provides consistent results across 3 different genetically informative approaches, strengthening the hypothesis that ADHD is causally related to MDD.
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Affiliation(s)
- Miguel Garcia-Argibay
- School of Medical Sciences, Örebro University, Faculty of Medicine and Health, Örebro, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Isabell Brikell
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | - Ditte Demontis
- Department of Biomedicine-Human Genetics, Aarhus University, Aarhus, Denmark; iPSYCH, Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Henrik Larsson
- School of Medical Sciences, Örebro University, Faculty of Medicine and Health, Örebro, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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17
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Arakelyan A, Avagyan S, Kurnosov A, Mkrtchyan T, Mkrtchyan G, Zakharyan R, Mayilyan KR, Binder H. Temporal changes of gene expression in health, schizophrenia, bipolar disorder, and major depressive disorder. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:19. [PMID: 38368435 PMCID: PMC10874418 DOI: 10.1038/s41537-024-00443-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 02/02/2024] [Indexed: 02/19/2024]
Abstract
The molecular events underlying the development, manifestation, and course of schizophrenia, bipolar disorder, and major depressive disorder span from embryonic life to advanced age. However, little is known about the early dynamics of gene expression in these disorders due to their relatively late manifestation. To address this, we conducted a secondary analysis of post-mortem prefrontal cortex datasets using bioinformatics and machine learning techniques to identify differentially expressed gene modules associated with aging and the diseases, determine their time-perturbation points, and assess enrichment with expression quantitative trait loci (eQTL) genes. Our findings revealed early, mid, and late deregulation of expression of functional gene modules involved in neurodevelopment, plasticity, homeostasis, and immune response. This supports the hypothesis that multiple hits throughout life contribute to disease manifestation rather than a single early-life event. Moreover, the time-perturbed functional gene modules were associated with genetic loci affecting gene expression, highlighting the role of genetic factors in gene expression dynamics and the development of disease phenotypes. Our findings emphasize the importance of investigating time-dependent perturbations in gene expression before the age of onset in elucidating the molecular mechanisms of psychiatric disorders.
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Affiliation(s)
- Arsen Arakelyan
- Institute of Molecular Biology NAS RA, Yerevan, Armenia.
- Armenian Bioinformatics Institute, Yerevan, Armenia.
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan, Armenia.
| | | | | | - Tigran Mkrtchyan
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan, Armenia
| | | | - Roksana Zakharyan
- Institute of Molecular Biology NAS RA, Yerevan, Armenia
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan, Armenia
| | - Karine R Mayilyan
- Institute of Molecular Biology NAS RA, Yerevan, Armenia
- Department of Therapeutics, Faculty of General Medicine, University of Traditional Medicine, Yerevan, Armenia
| | - Hans Binder
- Armenian Bioinformatics Institute, Yerevan, Armenia
- Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany
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18
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Cui L, Li S, Wang S, Wu X, Liu Y, Yu W, Wang Y, Tang Y, Xia M, Li B. Major depressive disorder: hypothesis, mechanism, prevention and treatment. Signal Transduct Target Ther 2024; 9:30. [PMID: 38331979 PMCID: PMC10853571 DOI: 10.1038/s41392-024-01738-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 12/24/2023] [Accepted: 12/28/2023] [Indexed: 02/10/2024] Open
Abstract
Worldwide, the incidence of major depressive disorder (MDD) is increasing annually, resulting in greater economic and social burdens. Moreover, the pathological mechanisms of MDD and the mechanisms underlying the effects of pharmacological treatments for MDD are complex and unclear, and additional diagnostic and therapeutic strategies for MDD still are needed. The currently widely accepted theories of MDD pathogenesis include the neurotransmitter and receptor hypothesis, hypothalamic-pituitary-adrenal (HPA) axis hypothesis, cytokine hypothesis, neuroplasticity hypothesis and systemic influence hypothesis, but these hypothesis cannot completely explain the pathological mechanism of MDD. Even it is still hard to adopt only one hypothesis to completely reveal the pathogenesis of MDD, thus in recent years, great progress has been made in elucidating the roles of multiple organ interactions in the pathogenesis MDD and identifying novel therapeutic approaches and multitarget modulatory strategies, further revealing the disease features of MDD. Furthermore, some newly discovered potential pharmacological targets and newly studied antidepressants have attracted widespread attention, some reagents have even been approved for clinical treatment and some novel therapeutic methods such as phototherapy and acupuncture have been discovered to have effective improvement for the depressive symptoms. In this work, we comprehensively summarize the latest research on the pathogenesis and diagnosis of MDD, preventive approaches and therapeutic medicines, as well as the related clinical trials.
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Affiliation(s)
- Lulu Cui
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Shu Li
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Siman Wang
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Xiafang Wu
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Yingyu Liu
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Weiyang Yu
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Yijun Wang
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Yong Tang
- International Joint Research Centre on Purinergic Signalling/Key Laboratory of Acupuncture for Senile Disease (Chengdu University of TCM), Ministry of Education/School of Health and Rehabilitation, Chengdu University of Traditional Chinese Medicine/Acupuncture and Chronobiology Key Laboratory of Sichuan Province, Chengdu, China
| | - Maosheng Xia
- Department of Orthopaedics, The First Hospital, China Medical University, Shenyang, China.
| | - Baoman Li
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China.
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China.
- China Medical University Centre of Forensic Investigation, Shenyang, China.
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Huider F, Milaneschi Y, Hottenga JJ, Bot M, Rietman ML, Kok AAL, Galesloot TE, 't Hart LM, Rutters F, Blom MT, Rhebergen D, Visser M, Brouwer I, Feskens E, Hartman CA, Oldehinkel AJ, de Geus EJC, Kiemeney LA, Huisman M, Picavet HSJ, Verschuren WMM, van Loo HM, Penninx BWJH, Boomsma DI. Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project. Twin Res Hum Genet 2024; 27:1-11. [PMID: 38497097 DOI: 10.1017/thg.2024.4] [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] [Indexed: 03/19/2024]
Abstract
In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.
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Affiliation(s)
- Floris Huider
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
| | - Yuri Milaneschi
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
| | - Mariska Bot
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - M Liset Rietman
- Center for Prevention, Lifestyle and Health, Dutch National Institute for Public Health and the Environment, 3721 Bilthoven, the Netherlands
| | - Almar A L Kok
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC location Vrije Universiteit, 1081 Amsterdam, the Netherlands
| | | | | | | | | | - Didi Rhebergen
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Mental health Institute GGZ Centraal, Amersfoort, the Netherlands
| | - Marjolein Visser
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Ingeborg Brouwer
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Edith Feskens
- Division of Human Nutrition and Health, Wageningen University & Research, 6700 Wageningen, the Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands
| | - Albertine J Oldehinkel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
| | | | - Martijn Huisman
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC location Vrije Universiteit, 1081 Amsterdam, the Netherlands
- Department of Sociology, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - H Susan J Picavet
- Center for Prevention, Lifestyle and Health, Dutch National Institute for Public Health and the Environment, 3721 Bilthoven, the Netherlands
| | - W M Monique Verschuren
- Center for Prevention, Lifestyle and Health, Dutch National Institute for Public Health and the Environment, 3721 Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 Utrecht, the Netherlands
| | - Hanna M van Loo
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands
| | - Brenda W J H Penninx
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, 1081 Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, 1105 Amsterdam, the Netherlands
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Wang W, Wang M, Peng H, Huang J, Wu T. Association of major depressive disorder and increased risk of irritable bowel syndrome: A population-based cohort study and a two-sample Mendelian randomization study in the UK biobank. J Affect Disord 2024; 345:419-426. [PMID: 37852586 DOI: 10.1016/j.jad.2023.10.111] [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: 06/28/2023] [Revised: 10/08/2023] [Accepted: 10/15/2023] [Indexed: 10/20/2023]
Abstract
OBJECTIVE To examine the association between depression and the risk of incident irritable bowel syndrome (IBS). METHODS We included 98,564 participants free of IBS in the UK biobank. Depression was defined by self-report and Hospital Episode Statistics. The main outcome was incident IBS. Cox proportional hazards regression models and two-sample mendelian randomization were performed to estimate the risk of incident IBS. RESULTS Among 98,564 participants, 8770 (8.9 %) participants had a depression diagnosis at baseline. During a median of 12.9-year follow-up, 224 cases of incident IBS were identified in patients with depression (2.0 per 1000 person-years), compared with 1625 cases in reference individuals (1.5 per 1000 person-years). After adjustment, the hazard ratio of incident IBS associated with depression was 1.26 (95 % CI: 1.01-1.41). Sensitivity analysis indicated similar results. The two-sample mendelian randomization based on the inverse variance weighted method provided evidence for the harmful role of depression in an increased risk of IBS with an OR of 1.57 (95 % CI: 1.24-1.99). LIMITATIONS Depression was mainly measured by self-report online CIDI-SF in the current study, rather than the gold diagnostic criteria including clinical structured interview, which might lead to potential measurement error. Lifestyle behaviors might change during the long-term follow-up, and time-varying covariates (i.e., smoking and alcohol status) may bias the estimate. CONCLUSIONS Depression is associated with an increased risk of incident IBS. Further studies are warranted to confirm the role of depression on incident IBS and elucidate the underlying mechanisms.
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Affiliation(s)
- Weiwei Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing 100191, China; Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, 5 Ankang Lane, Xicheng District, Beijing 100088, China
| | - Mengying Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing 100191, China
| | - Hexiang Peng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing 100191, China
| | - Jie Huang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen 518055, China.
| | - Tao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing 100191, China.
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21
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Cavanagh JT. Anti-inflammatory Drugs in the Treatment of Depression. Curr Top Behav Neurosci 2024; 66:217-231. [PMID: 38112963 DOI: 10.1007/7854_2023_459] [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] [Indexed: 12/21/2023]
Abstract
The last two decades have seen a flourishing of research into the immunobiology of psychiatric phenotypes, in particular major depressive disorder. Both preclinical and clinical data have highlighted pathways and possible mechanisms that might link changes in immunobiology, most especially inflammation, to clinically relevant behaviour. From a therapeutics perspective, a major impetus has been the action of Biologics, often monoclonal antibodies, that target specific cytokines acting as "molecular scalpels" helping to uncover the actions of those proteins. These interventions have been associated with improvements in mood and related symptoms. There are now enough studies and participants to permit meta-analytic analyses of the actions of these and other anti-inflammatory agents.In this chapter, the focus is on the evidence for the role of inflammation biology in depression and the meta-analytic data from trials. The putative mechanisms that might underpin the antidepressant effect of anti-inflammatory drugs are also explored. Lastly, I describe the more stubborn difficulties around heterogeneity, deep phenotyping and stratification as well as improved animal models and greater understanding of the biology that might be addressed by future studies.
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Affiliation(s)
- Jonathan T Cavanagh
- Centre for Immunobiology, School of Infection and Immunity, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
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22
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Dahl A, Thompson M, An U, Krebs M, Appadurai V, Border R, Bacanu SA, Werge T, Flint J, Schork AJ, Sankararaman S, Kendler KS, Cai N. Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. Nat Genet 2023; 55:2082-2093. [PMID: 37985818 PMCID: PMC10703686 DOI: 10.1038/s41588-023-01559-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/18/2023] [Indexed: 11/22/2023]
Abstract
Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.
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Affiliation(s)
- Andrew Dahl
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA.
| | - Michael Thompson
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ulzee An
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Morten Krebs
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
| | - Vivek Appadurai
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
| | - Richard Border
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Silviu-Alin Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
- Lundbeck Foundation GeoGenetics Centre, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jonathan Flint
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Sriram Sankararaman
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany.
- Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany.
- School of Medicine, Technical University of Munich, Munich, Germany.
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23
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Ogata H, Higasa K, Kageyama Y, Tahara H, Shimamoto A, Takekita Y, Koshikawa Y, Nonen S, Kato T, Kinoshita T, Kato M. Relationship between circulating mitochondrial DNA and microRNA in patients with major depression. J Affect Disord 2023; 339:538-546. [PMID: 37467797 DOI: 10.1016/j.jad.2023.07.073] [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: 02/28/2023] [Revised: 06/22/2023] [Accepted: 07/14/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND MicroRNAs (miRNAs) and circulating cell-free mitochondrial DNA (ccf-mtDNA) have attracted interest as biological markers of affective disorders. In response to stress, it is known that miRNAs in mitochondria diffuse out of the cytoplasm alongside mtDNA; however, this process has not yet been identified. We hypothesized that miRNAs derived from specific cell nuclei cause mitochondrial damage and mtDNA fragmentation under MDD-associated stress conditions. METHODS A comprehensive analysis of the plasma miRNA levels and quantification of the plasma ccf-mtDNA copy number were performed in 69 patients with depression to determine correlations and identify genes and pathways interacting with miRNAs. The patients were randomly assigned to receive either selective serotonin reuptake inhibitors (SSRI) or mirtazapine. Their therapeutic efficacy over four weeks was evaluated in relation to miRNAs correlated with ccf-mtDNA copy number. RESULTS The expression levels of the five miRNAs showed a significant positive correlation with the ccf-mtDNA copy number after correcting for multiple testing. These miRNAs are involved in gene expression related to thyroid hormone synthesis, the Hippo signaling pathway, vasopressin-regulated water reabsorption, and lysine degradation. Of these five miRNAs, miR-6068 and miR-4708-3p were significantly associated with the SSRI and mirtazapine treatment outcomes, respectively. LIMITATIONS This study did not show comparison with a healthy group. CONCLUSIONS The expression levels of specific miRNAs were associated with ccf-mtDNA copy number in untreated depressed patients; moreover, these miRNAs were linked to antidepressant treatment outcomes. These findings are expected to lead to the elucidation of new pathological mechanism of depression.
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Affiliation(s)
- Haruhiko Ogata
- Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan
| | - Koichiro Higasa
- Institute of Biomedical Science, Department of Genome Analysis, Kansai Medical University, Osaka, Japan
| | - Yuki Kageyama
- Department of Neuropsychiatry, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Hidetoshi Tahara
- Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Akira Shimamoto
- Faculty of Pharmaceutical Sciences, Sanyo-Onoda City University, Sanyo Onoda, Yamaguchi, Japan
| | | | - Yosuke Koshikawa
- Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan
| | - Shinpei Nonen
- Department of Pharmacy, Hyogo University of Health Sciences, Hyogo, Japan
| | - Tadafumi Kato
- Department of Psychiatry & Behavioral Science, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | | | - Masaki Kato
- Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan.
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24
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Karageorgiou V, Casanova F, O'Loughlin J, Green H, McKinley TJ, Bowden J, Tyrrell J. Body mass index and inflammation in depression and treatment-resistant depression: a Mendelian randomisation study. BMC Med 2023; 21:355. [PMID: 37710313 PMCID: PMC10502981 DOI: 10.1186/s12916-023-03001-7] [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: 12/15/2022] [Accepted: 07/24/2023] [Indexed: 09/16/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) has a significant impact on global burden of disease. Complications in clinical management can occur when response to pharmacological modalities is considered inadequate and symptoms persist (treatment-resistant depression (TRD)). We aim to investigate inflammation, proxied by C-reactive protein (CRP) levels, and body mass index (BMI) as putative causal risk factors for depression and subsequent treatment resistance, leveraging genetic information to avoid confounding via Mendelian randomisation (MR). METHODS We used the European UK Biobank subcohort ([Formula: see text]), the mental health questionnaire (MHQ) and clinical records. For treatment resistance, a previously curated phenotype based on general practitioner (GP) records and prescription data was employed. We applied univariable and multivariable MR models to genetically predict the exposures and assess their causal contribution to a range of depression outcomes. We used a range of univariable, multivariable and mediation MR models techniques to address our research question with maximum rigour. In addition, we developed a novel statistical procedure to apply pleiotropy-robust multivariable MR to one sample data and employed a Bayesian bootstrap procedure to accurately quantify estimate uncertainty in mediation analysis which outperforms standard approaches in sparse binary outcomes. Given the flexibility of the one-sample design, we evaluated age and sex as moderators of the effects. RESULTS In univariable MR models, genetically predicted BMI was positively associated with depression outcomes, including MDD ([Formula: see text] ([Formula: see text] CI): 0.133(0.072, 0.205)) and TRD (0.347(0.002, 0.682)), with a larger magnitude in females and with age acting as a moderator of the effect of BMI on severity of depression (0.22(0.050, 0.389)). Multivariable MR analyses suggested an independent causal effect of BMI on TRD not through CRP (0.395(0.004, 0.732)). Our mediation analyses suggested that the effect of CRP on severity of depression was partly mediated by BMI. Individuals with TRD ([Formula: see text]) observationally had higher CRP and BMI compared with individuals with MDD alone and healthy controls. DISCUSSION Our work supports the assertion that BMI exerts a causal effect on a range of clinical and questionnaire-based depression phenotypes, with the effect being stronger in females and in younger individuals. We show that this effect is independent of inflammation proxied by CRP levels as the effects of CRP do not persist when jointly estimated with BMI. This is consistent with previous evidence suggesting that overweight contributed to depression even in the absence of any metabolic consequences. It appears that BMI exerts an effect on TRD that persists when we account for BMI influencing MDD.
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Affiliation(s)
| | | | | | - Harry Green
- College of Medicine & Health, University of Exeter, Exeter, UK
| | | | - Jack Bowden
- College of Medicine & Health, University of Exeter, Exeter, UK
- Genetics Department, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Jessica Tyrrell
- College of Medicine & Health, University of Exeter, Exeter, UK
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25
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van Loo HM, de Vries YA, Taylor J, Todorovic L, Dollinger C, Kendler KS. Clinical characteristics indexing genetic differences in bipolar disorder - a systematic review. Mol Psychiatry 2023; 28:3661-3670. [PMID: 37968345 DOI: 10.1038/s41380-023-02297-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 09/29/2023] [Accepted: 10/06/2023] [Indexed: 11/17/2023]
Abstract
Bipolar disorder is a heterogenous condition with a varied clinical presentation. While progress has been made in identifying genetic variants associated with bipolar disorder, most common genetic variants have not yet been identified. More detailed phenotyping (beyond diagnosis) may increase the chance of finding genetic variants. Our aim therefore was to identify clinical characteristics that index genetic differences in bipolar disorder.We performed a systematic review of all genome-wide molecular genetic, family, and twin studies investigating familial/genetic influences on the clinical characteristics of bipolar disorder. We performed an electronic database search of PubMed and PsycInfo until October 2022. We reviewed title/abstracts of 2693 unique records and full texts of 391 reports, identifying 445 relevant analyses from 142 different reports. These reports described 199 analyses from family studies, 183 analyses from molecular genetic studies and 63 analyses from other types of studies. We summarized the overall evidence per phenotype considering study quality, power, and number of studies.We found moderate to strong evidence for a positive association of age at onset, subtype (bipolar I versus bipolar II), psychotic symptoms and manic symptoms with familial/genetic risk of bipolar disorder. Sex was not associated with overall genetic risk but could indicate qualitative genetic differences. Assessment of genetically relevant clinical characteristics of patients with bipolar disorder can be used to increase the phenotypic and genetic homogeneity of the sample in future genetic studies, which may yield more power, increase specificity, and improve understanding of the genetic architecture of bipolar disorder.
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Affiliation(s)
- Hanna M van Loo
- Department of Psychiatry and Interdisciplinary Center Psychopathology and Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
| | - Ymkje Anna de Vries
- Department of Child and Adolescent Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jacob Taylor
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Luka Todorovic
- Department of Psychiatry and Interdisciplinary Center Psychopathology and Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Child and Adolescent Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Camille Dollinger
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
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26
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Zarbo C, Rota M, Calza S, Crouter SE, Ekelund U, Barlati S, Bussi R, Clerici M, Placenti R, Paulillo G, Pogliaghi S, Rocchetti M, Ruggeri M, Starace F, Zanolini S, Zamparini M, de Girolamo G. Ecological monitoring of physical activity, emotions and daily life activities in schizophrenia: the DiAPAson study. BMJ MENTAL HEALTH 2023; 26:e300836. [PMID: 37666578 PMCID: PMC11146405 DOI: 10.1136/bmjment-2023-300836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 08/22/2023] [Indexed: 09/06/2023]
Abstract
BACKGROUND Schizophrenia spectrum disorders (SSD) compromise psychosocial functioning, including daily time use, emotional expression and physical activity (PA). OBJECTIVE We performed a cohort study aimed at investigating: (1) the differences in PA, daily activities and emotions between patients with SSD and healthy controls (HC); (2) the strength of the association between these variables and clinical features among patients with SSD. METHODS Ninety-nine patients with SSD (53 residential patients, 46 outpatients) and 111 matched HC were assessed for several clinical variables, and levels of functioning by means of standardised clinical measures. Self-reported daily activities and emotions were assessed with a smartphone application for ecological momentary assessment (EMA), and PA levels were assessed with a wearable accelerometer for 7 consecutive days.FindingsPatients with SSD, especially those living in residential facilities, spent more time being sedentary, and self-reported more sedentary and self-care activities, experiencing higher levels of negative emotions compared with HC. Moreover, higher functioning levels among patients were associated with more time spent in moderate-to-vigorous activity. CONCLUSIONS Sedentary behaviour and negative emotions are particularly critical among patients with SSD and are associated with more impaired clinical outcomes. CLINICAL IMPLICATIONS Mobile-EMA and wearable sensors are useful for monitoring the daily life of patients with SSD and the level of PA. This population needs to be targeted with specific rehabilitative programmes aimed at improving their commitment to structured daily activities.
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Affiliation(s)
- Cristina Zarbo
- Department of Psychology, University of Milan-Bicocca, Milano, Italy
| | - Matteo Rota
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Stefano Calza
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Scott E Crouter
- Department of Kinesiology, Recreation, and Sport Studies, The University of Tennessee Knoxville, Knoxville, Tennessee, USA
| | - Ulf Ekelund
- Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
- Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway
| | - Stefano Barlati
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Riccardo Bussi
- Centro Sant'Ambrogio-Fatebenefratelli, Cernusco sul Naviglio, Italy
| | - Massimo Clerici
- Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy
| | - Roberto Placenti
- Centro Sacro Cuore di Gesù Fatebenefratelli, San Colombano al Lambro, Italy
| | - Giuseppina Paulillo
- Department of Mental Health and Pathological Addiction, Azienda USL di Parma, Parma, Italy
| | - Silvia Pogliaghi
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | | | - Mirella Ruggeri
- Department of Psychiatry, Verona Hospital Trust, AOUI, Verona, Italy
| | - Fabrizio Starace
- Department of Mental Health and Dependence, AUSL Modena, Modena, Italy
| | - Stefano Zanolini
- Department of Mental Health and Dependence, Azienda ULSS 8 Berica, Vicenza, Italy
| | - Manuel Zamparini
- Unit of Epidemiological and Evaluation Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni de Girolamo
- Unit of Epidemiological and Evaluation Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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27
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Funatsuki T, Ogata H, Tahara H, Shimamoto A, Takekita Y, Koshikawa Y, Nonen S, Higasa K, Kinoshita T, Kato M. Changes in Multiple microRNA Levels with Antidepressant Treatment Are Associated with Remission and Interact with Key Pathways: A Comprehensive microRNA Analysis. Int J Mol Sci 2023; 24:12199. [PMID: 37569574 PMCID: PMC10418406 DOI: 10.3390/ijms241512199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/26/2023] [Accepted: 07/29/2023] [Indexed: 08/13/2023] Open
Abstract
Individual treatment outcomes to antidepressants varies widely, yet the determinants to this difference remain elusive. MicroRNA (miRNA) gene expression regulation in major depressive disorder (MDD) has attracted interest as a biomarker. This 4-week randomized controlled trial examined changes in the plasma miRNAs that correlated with the treatment outcomes of mirtazapine (MIR) and selective serotonin reuptake inhibitor (SSRI) monotherapy. Pre- and post- treatment, we comprehensively analyzed the miRNA levels in MDD patients, and identified the gene pathways linked to these miRNAs in 46 patients. Overall, 141 miRNA levels significantly demonstrated correlations with treatment remission after 4 weeks of MIR, with miR-1237-5p showing the most robust and significant correlation after Bonferroni correction. These 141 miRNAs displayed a negative correlation with remission, indicating a decreasing trend. These miRNAs were associated with 15 pathways, including TGF-β and MAPK. Through database searches, the genes targeted by these miRNAs with the identified pathways were compared, and it was found that MAPK1, IGF1, IGF1R, and BRAF matched. Alterations in specific miRNAs levels before and after MIR treatment correlated with remission. The miRNAs mentioned in this study have not been previously reported. No other studies have investigated treatment with MIR. The identified miRNAs also correlated with depression-related genes and pathways.
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Affiliation(s)
- Toshiya Funatsuki
- Department of Neuropsychiatry, Kansai Medical University, Osaka 573-1191, Japan; (T.F.); (H.O.); (Y.T.); (Y.K.); (T.K.)
| | - Haruhiko Ogata
- Department of Neuropsychiatry, Kansai Medical University, Osaka 573-1191, Japan; (T.F.); (H.O.); (Y.T.); (Y.K.); (T.K.)
| | - Hidetoshi Tahara
- Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima 734-8533, Japan;
| | - Akira Shimamoto
- Faculty of Pharmaceutical Sciences, Sanyo-Onoda City University, Sanyo-Onoda 756-0084, Japan;
| | - Yoshiteru Takekita
- Department of Neuropsychiatry, Kansai Medical University, Osaka 573-1191, Japan; (T.F.); (H.O.); (Y.T.); (Y.K.); (T.K.)
| | - Yosuke Koshikawa
- Department of Neuropsychiatry, Kansai Medical University, Osaka 573-1191, Japan; (T.F.); (H.O.); (Y.T.); (Y.K.); (T.K.)
| | - Shinpei Nonen
- Department of Pharmacy, Hyogo Medical University, Nishinomiya 650-8530, Japan;
| | - Koichiro Higasa
- Institute of Biomedical Science, Department of Genome Analysis, Kansai Medical University, Osaka 573-1191, Japan;
| | - Toshihiko Kinoshita
- Department of Neuropsychiatry, Kansai Medical University, Osaka 573-1191, Japan; (T.F.); (H.O.); (Y.T.); (Y.K.); (T.K.)
| | - Masaki Kato
- Department of Neuropsychiatry, Kansai Medical University, Osaka 573-1191, Japan; (T.F.); (H.O.); (Y.T.); (Y.K.); (T.K.)
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28
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Chung IH, Huang YS, Fang TH, Chen CH. Whole Genome Sequencing Revealed Inherited Rare Oligogenic Variants Contributing to Schizophrenia and Major Depressive Disorder in Two Families. Int J Mol Sci 2023; 24:11777. [PMID: 37511534 PMCID: PMC10380944 DOI: 10.3390/ijms241411777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/12/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
Schizophrenia and affective disorder are two major complex mental disorders with high heritability. Evidence shows that rare variants with significant clinical impacts contribute to the genetic liability of these two disorders. Also, rare variants associated with schizophrenia and affective disorders are highly personalized; each patient may carry different variants. We used whole genome sequencing analysis to study the genetic basis of two families with schizophrenia and major depressive disorder. We did not detect de novo, autosomal dominant, or recessive pathogenic or likely pathogenic variants associated with psychiatric disorders in these two families. Nevertheless, we identified multiple rare inherited variants with unknown significance in the probands. In family 1, with singleton schizophrenia, we detected four rare variants in genes implicated in schizophrenia, including p.Arg1627Trp of LAMA2, p.Pro1338Ser of CSMD1, p.Arg691Gly of TLR4, and Arg182X of AGTR2. The p.Arg691Gly of TLR4 was inherited from the father, while the other three were inherited from the mother. In family 2, with two affected sisters diagnosed with major depressive disorder, we detected three rare variants shared by the two sisters in three genes implicated in affective disorders, including p.Ala4551Gly of FAT1, p.Val231Leu of HOMER3, and p.Ile185Met of GPM6B. These three rare variants were assumed to be inherited from their parents. Prompted by these findings, we suggest that these rare inherited variants may interact with each other and lead to psychiatric conditions in these two families. Our observations support the conclusion that inherited rare variants may contribute to the heritability of psychiatric disorders.
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Affiliation(s)
- I-Hang Chung
- Department of Psychiatry, Chang Gung Memorial Hospital-Linkou, Taoyuan 333, Taiwan
| | - Yu-Shu Huang
- Department of Psychiatry, Chang Gung Memorial Hospital-Linkou, Taoyuan 333, Taiwan
- Department of Psychiatry, College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
| | - Ting-Hsuan Fang
- Department of Psychiatry, Chang Gung Memorial Hospital-Linkou, Taoyuan 333, Taiwan
| | - Chia-Hsiang Chen
- Department of Psychiatry, Chang Gung Memorial Hospital-Linkou, Taoyuan 333, Taiwan
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Adams MJ, Thorp JG, Jermy BS, Kwong ASF, Kõiv K, Grotzinger AD, Nivard MG, Marshall S, Milaneschi Y, Baune BT, Müller-Myhsok B, Penninx BW, Boomsma DI, Levinson DF, Breen G, Pistis G, Grabe HJ, Tiemeier H, Berger K, Rietschel M, Magnusson PK, Uher R, Hamilton SP, Lucae S, Lehto K, Li QS, Byrne EM, Hickie IB, Martin NG, Medland SE, Wray NR, Tucker-Drob EM, Lewis CM, McIntosh AM, Derks EM. Genetic structure of major depression symptoms across clinical and community cohorts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.05.23292214. [PMID: 37461564 PMCID: PMC10350129 DOI: 10.1101/2023.07.05.23292214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and aetiological subtypes. There are several challenges to integrating symptom data from genetically-informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data. We conducted genome-wide association studies of major depressive symptoms in three clinical cohorts that were enriched for affected participants (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors. The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for missing data patterns in the community cohorts (use of Depression and Anhedonia as gating symptoms). The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analysing genetic association data.
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Affiliation(s)
- Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Jackson G Thorp
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, AU
| | - Bradley S Jermy
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, FI
| | - Alex S F Kwong
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Kadri Kõiv
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, EE
| | - Andrew D Grotzinger
- Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, CO, US
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, US
| | - Michel G Nivard
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Sally Marshall
- Centre for Genomic & Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Bernhard T Baune
- Department of Psychiatry, University of Melbourne, Melbourne, VIC, AU
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, AU
- Department of Psychiatry, University of Münster, Münster, NRW, DE
| | - Bertram Müller-Myhsok
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, BY, DE
- Munich Cluster for Systems Neurology (SyNergy), Munich, BY, DE
- Institute of Population Health, University of Liverpool, Liverpool, UK
| | - Brenda Wjh Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Dorret I Boomsma
- Department of Biological Psychology & Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Douglas F Levinson
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, US
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, King's College London, London, UK
| | - Giorgio Pistis
- Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, VD, CH
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald MV, DE
| | - Henning Tiemeier
- Child and Adolescent Psychiatry, Erasmus University Medical Center Rotterdam, Rotterdam, NL
- Social and Behavioral Science, Harvard T.H. Chan School of Public Health, Boston, MA, US
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, NRW, DE
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, BW, DE
| | - Patrik K Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, SE
| | - Rudolf Uher
- Psychiatry, Dalhousie University, Halifax, NS, CA
| | - Steven P Hamilton
- Psychiatry, Kaiser Permanente Northern California, San Francisco, CA, US
| | | | - Kelli Lehto
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, EE
| | - Qingqin S Li
- Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, NJ, US
| | - Enda M Byrne
- Child Health Research Centre, University of Queensland, Brisbane, QLD, AU
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, NSW, AU
| | - Nicholas G Martin
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, AU
| | - Sarah E Medland
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, AU
| | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, AU
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, AU
| | - Elliot M Tucker-Drob
- Department of Psychology, University of Texas at Austin, Austin, TX, US
- Population Research Center, University of Texas at Austin, Austin, TX, US
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
- Department of Medical & Molecular Genetics, King's College London, London, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Institute for Genomics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Eske M Derks
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, AU
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Markov DD, Dolotov OV, Grivennikov IA. The Melanocortin System: A Promising Target for the Development of New Antidepressant Drugs. Int J Mol Sci 2023; 24:ijms24076664. [PMID: 37047638 PMCID: PMC10094937 DOI: 10.3390/ijms24076664] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/27/2023] [Accepted: 03/30/2023] [Indexed: 04/05/2023] Open
Abstract
Major depression is one of the most prevalent mental disorders, causing significant human suffering and socioeconomic loss. Since conventional antidepressants are not sufficiently effective, there is an urgent need to develop new antidepressant medications. Despite marked advances in the neurobiology of depression, the etiology and pathophysiology of this disease remain poorly understood. Classical and newer hypotheses of depression suggest that an imbalance of brain monoamines, dysregulation of the hypothalamic-pituitary-adrenal axis (HPAA) and immune system, or impaired hippocampal neurogenesis and neurotrophic factors pathways are cause of depression. It is assumed that conventional antidepressants improve these closely related disturbances. The purpose of this review was to discuss the possibility of affecting these disturbances by targeting the melanocortin system, which includes adrenocorticotropic hormone-activated receptors and their peptide ligands (melanocortins). The melanocortin system is involved in the regulation of various processes in the brain and periphery. Melanocortins, including peripherally administered non-corticotropic agonists, regulate HPAA activity, exhibit anti-inflammatory effects, stimulate the levels of neurotrophic factors, and enhance hippocampal neurogenesis and neurotransmission. Therefore, endogenous melanocortins and their analogs are able to complexly affect the functioning of those body’s systems that are closely related to depression and the effects of antidepressants, thereby demonstrating a promising antidepressant potential.
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Affiliation(s)
- Dmitrii D. Markov
- National Research Center “Kurchatov Institute”, Kurchatov Sq. 2, 123182 Moscow, Russia
| | - Oleg V. Dolotov
- National Research Center “Kurchatov Institute”, Kurchatov Sq. 2, 123182 Moscow, Russia
- Faculty of Biology, Lomonosov Moscow State University, Leninskie Gory, 119234 Moscow, Russia
| | - Igor A. Grivennikov
- National Research Center “Kurchatov Institute”, Kurchatov Sq. 2, 123182 Moscow, Russia
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