Megjegyzés: Abstracts of the World Congress of Psychiatric Genetics (WCPG), October 19-23, 2025

Megjegyzés: Funding Agency and Grant Number: Hungarian National Research, Development, and Innovation Office [K 139330, PD 146014, PD 134449]; Hungarian Brain Research Program 3.0 [NAP2022-I-4/2022]; Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund [TKP2021-EGA-25, TKP2021-EGA-02]; European Union [RRF-2.3.1-21-2022-00004]; Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences; Academy of Finland [ERAPERMED2019-108]; Catalan Department of Health [ERAPERMED2019-108, SLD002/19/000002];  [2019-2.1.7-ERA-NET-2020-00005];  [OTKA K 143391];  [EKOP-2024-68]
            Funding text: This study was supported by the Hungarian National Research, Development, and Innovation Office 2019-2.1.7-ERA-NET-2020-00005 under the frame of ERA PerMed (ERAPERMED2019-108) ; by the Hungarian National Research, Development, and Innovation Office OTKA K 143391, K 139330, PD 146014, and PD 134449 grants; by the Hungarian Brain Research Program 3.0 (NAP2022-I-4/2022) ; and by TKP2021-EGA-25 and TKP2021-EGA-02, supported by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, under the TKP2021-EGA funding scheme; and the European Union project [RRF-2.3.1-21-2022-00004] within the framework of the Artificial Intelligence National Laboratory. Dora Torok is supported by EKOP-2024-68. Nora Eszlari is supported by the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences. The study was funded by the Academy of Finland under the frame of ERA PerMed (TRAJECTOME project, ERAPERMED2019-108) . The Catalan cohort was extracted from the Catalan Health Surveillance System database, owned and managed by the Catalan Health Service, with the earnest collaboration of the Digitalization for the Sustainability of the Healthcare (DS3) -IDIBELL group. The study was supported by the Catalan Department of Health (SLD002/19/000002) under the frame of ERA PerMed (ERAPERMED2019-108) .

Megjegyzés: Department of Artificial Intelligence and Systems Engineering, Budapest University of Technology and Economics, Budapest, Hungary            
            Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany            
            German Centre for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany            
            Department of Public Health and Welfare, Population Health Unit, Public Health Research Team, Finnish Institute for Health and Welfare, Helsinki, Finland            
            Department of Pharmacodynamics, Faculty of Pharmaceutical Sciences, Semmelweis University, Budapest, Hungary            
            NAP3.0-SE Neuropsychopharmacology Research Group, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary            
            Clínic Barcelona, Fundació de Recerca Clinic Barcelona - Institut d’Investigacions Biomèdiques August Pi i Sunyer (FRCB-IDIBAPS), Universitat de Barcelona, Barcelona, Spain            
            Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary            
            Abiomics Europe Ltd., Budapest, Hungary            
            Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany            
            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, Helsinki, Finland            
            Export Date: 3 September 2024            
            Correspondence Address: Juhasz, G.; Department of Pharmacodynamics, Hungary; email: juhasz.gabriella@semmelweis.hu

Megjegyzés: Funding Agency and Grant Number: European Research Area on Personalized Medicine (ERA PerMed) program [ERAPERMED2019-108]; Academy of Finland; Hungarian National Research, Development, and Innovation Office [2019-2.1.7-ERA-NET-2020-00005K143391, K139330, PD 134449]; Hungarian Brain Research Program 3.0 [NAP2022-I-4/2022]; Ministry for Innovation and Technology of Hungary from the National Research, Development, and Innovation Fund under the TKP2021-EGA [TKP2021-EGA-25, TKP2021-EGA-02]; European Union [RRF-2.3.1-21-2022-00004]
            Funding text: This initiative was supported by European Research Area on Personalized Medicine (ERA PerMed) program ("Temporal disease map based stratification of depression-related multimorbidities: towards quantitative investigations of patient trajectories and predictions of multi-target drug candidates" [TRAJECTOME] project; ERAPERMED2019-108) . Locally, this study was supported by the Academy of Finland under the frame of the ERA PerMed program and the Hungarian National Research, Development, and Innovation Office (2019-2.1.7-ERA-NET-2020-00005K143391, K139330 and PD 134449 grants) ; the Hungarian Brain Research Program 3.0 (NAP2022-I-4/2022) ; and the Ministry for Innovation and Technology of Hungary from the National Research, Development, and Innovation Fund under the TKP2021-EGA funding scheme (TKP2021-EGA-25 and TKP2021-EGA-02) . This study was supported by the European Union project RRF-2.3.1-21-2022-00004 within the framework of the Artificial Intelligence National Laboratory. The authors want to acknowledge the earnest collaboration of the Digitalization for the Sustainability of the Healthcare System research group at Institut d'Investigacio Biomedica de Bellvitge (IDIBELL) for their support in the preparation of the Catalan cohort, which was extracted from the Catalan Health Surveillance System database, owned and managed by the Catalan Health Service. In addition, the authors want to acknowledge the participants and investigators of the FinnGen study and CSC-IT Center for Science, Finland, for computational resources. This research was conducted using the UK Biobank resource under application 1602. Linked health data Copyright 2019, NHS England. Reused with the permission of the UK Biobank. All rights reserved.

Megjegyzés: Funding Agency and Grant Number: Hungarian National Research, Development and Innovation Office [2020-1.1.2-PIACI-KFI-2021-00291];  [TKP2021-EGA-02]
            Funding text: The research presented in this paper has been performed as part of the MAIA - Medical AI Assistant development project of Gamax Laboratory Solutions, supported by grant 2020-1.1.2-PIACI-KFI-2021-00291 of the Hungarian National Research, Development and Innovation Office, and also by grant TKP2021-EGA-02.
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