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Viant MR, Amstalden E, Athersuch T, Bouhifd M, Camuzeaux S, Crizer DM, Driemert P, Ebbels T, Ekman D, Flick B, Giri V, Gómez-Romero M, Haake V, Herold M, Kende A, Lai F, Leonards PEG, Lim PP, Lloyd GR, Mosley J, Namini C, Rice JR, Romano S, Sands C, Smith MJ, Sobanski T, Southam AD, Swindale L, van Ravenzwaay B, Walk T, Weber RJM, Zickgraf FM, Kamp H. Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice. Arch Toxicol 2024; 98:1111-1123. [PMID: 38368582 PMCID: PMC10944399 DOI: 10.1007/s00204-024-03680-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 01/15/2024] [Indexed: 02/19/2024]
Abstract
While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography-mass spectrometry (LC-MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.
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Affiliation(s)
- Mark R Viant
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
| | - E Amstalden
- Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
| | - T Athersuch
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK
| | - M Bouhifd
- European Chemicals Agency, Telakkakatu 6, FI-00121, Helsinki, Finland
| | - S Camuzeaux
- Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, W12 0NN, UK
| | - D M Crizer
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA
| | - P Driemert
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
| | - T Ebbels
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK
| | - D Ekman
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Athens, GA, 30605, USA
| | - B Flick
- BASF SE, Carl-Bosch-Str 38, 67056, Ludwigshafen, Germany
- NUVISAN ICB GmbH, Toxicology, 13353, Berlin, Germany
| | - V Giri
- BASF SE, Carl-Bosch-Str 38, 67056, Ludwigshafen, Germany
| | - M Gómez-Romero
- Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, W12 0NN, UK
| | - V Haake
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
| | - M Herold
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
| | - A Kende
- Syngenta, Jealott's Hill International Research Centre, Bracknell, RG42 6EY, UK
| | - F Lai
- Syngenta, Jealott's Hill International Research Centre, Bracknell, RG42 6EY, UK
| | - P E G Leonards
- Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
| | - P P Lim
- Syngenta, Jealott's Hill International Research Centre, Bracknell, RG42 6EY, UK
| | - G R Lloyd
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - J Mosley
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Athens, GA, 30605, USA
| | - C Namini
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Athens, GA, 30605, USA
| | - J R Rice
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA
| | - S Romano
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Athens, GA, 30605, USA
| | - C Sands
- Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, W12 0NN, UK
| | - M J Smith
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - T Sobanski
- European Chemicals Agency, Telakkakatu 6, FI-00121, Helsinki, Finland
| | - A D Southam
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - L Swindale
- Syngenta, Jealott's Hill International Research Centre, Bracknell, RG42 6EY, UK
| | - B van Ravenzwaay
- BASF SE, Carl-Bosch-Str 38, 67056, Ludwigshafen, Germany
- Environmental Sciences Consulting, 67122, Altrip, Germany
| | - T Walk
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
| | - R J M Weber
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - F M Zickgraf
- BASF SE, Carl-Bosch-Str 38, 67056, Ludwigshafen, Germany
| | - H Kamp
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
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Kastner U, Javaheripour N, Arand J, Schönherr D, Sobanski T, Fehler S, Walter M, Wagner G. Effects of the COVID-19 pandemic on suicide attempts in a rural region in Germany, a 5-year observational study. J Affect Disord 2022; 318:393-399. [PMID: 36113687 PMCID: PMC9472680 DOI: 10.1016/j.jad.2022.09.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 08/05/2022] [Accepted: 09/11/2022] [Indexed: 10/26/2022]
Abstract
BACKGROUND The COVID-19 pandemic and public life restrictions may have a negative impact on people's mental health. Therefore, we analyzed whether this condition affected the occurrence of suicide attempts (SA) over 20 months during the pandemic period. METHODS We included patient records according to DSM-5 criteria for suicidal behavior disorders (n = 825) between Jan 1, 2017, and Dec 31, 2021. We applied interrupted time-series Poisson regression models to investigate the effect of the pandemic on SA occurrence, time trends, and seasonal patterns in the whole group of patients as well as stratified by age and gender. RESULTS There was no significant effect of the pandemic on the occurrence of SA in the overall group. However, we observed a significant impact of the pandemic on the seasonal pattern of SA, also the variance differed significantly (pre-pandemic mean ± variance: 13.33 ± 15.75, pandemic: mean ± variance: 13.86 ± 7.26), indicating less periodic variation in SA during the pandemic. Male patients and young adults mainly contributed to this overall effect. Subgroup analysis revealed a significant difference in SA trends during the pandemic in older adults (>55 years) compared with younger adults (18-35 years); SA numbers increased in older adults and decreased in younger adults as the pandemic progressed. LIMITATIONS A few patients may have received initial care in an emergency department after SA without being referred to psychiatry. CONCLUSIONS In general, the COVID-19 pandemic and related measures did not significantly affect the occurrence of SA but did significantly affect the dynamics. In addition, the pandemic appeared to affect suicidal behavior differently across age groups as it progressed. Particularly for the older adult group, negative long-term effects of the pandemic on suicidal behavior can be derived from the present results, indicating the need to strengthen suicide prevention for the elderly.
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Affiliation(s)
- U.W. Kastner
- Department of Psychiatry and Psychotherapy, Helios Fachkliniken Hildburghausen, Eisfelder Str.41, 98646 Hildburghausen, Germany,Correspondence to: U.W. Kastner, Helios Fachkliniken Hildburghausen, Eisfelder Str.41, 98646 Hildburghausen, Germany
| | - N. Javaheripour
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - J. Arand
- Department of Psychiatry and Psychotherapy, Helios Fachkliniken Hildburghausen, Eisfelder Str.41, 98646 Hildburghausen, Germany
| | - D. Schönherr
- Department of Psychiatry and Psychotherapy, Helios Fachkliniken Hildburghausen, Eisfelder Str.41, 98646 Hildburghausen, Germany
| | - T. Sobanski
- Department of Psychiatry, Psychotherapy, and Psychosomatic Medicine, Thueringen-Kliniken GmbH, 07318 Saalfeld, Germany
| | - S.W. Fehler
- Department of Psychiatry and Psychotherapy, Helios Fachkliniken Hildburghausen, Eisfelder Str.41, 98646 Hildburghausen, Germany
| | - M. Walter
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - G. Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany,Correspondence to: G. Wagner, Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743 Jena, Germany
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Dimitrov SD, Diderich R, Sobanski T, Pavlov TS, Chankov GV, Chapkanov AS, Karakolev YH, Temelkov SG, Vasilev RA, Gerova KD, Kuseva CD, Todorova ND, Mehmed AM, Rasenberg M, Mekenyan OG. QSAR Toolbox - workflow and major functionalities. SAR QSAR Environ Res 2016; 27:203-219. [PMID: 26892800 DOI: 10.1080/1062936x.2015.1136680] [Citation(s) in RCA: 87] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
The OECD QSAR Toolbox is a software application intended to be used by governments, the chemical industry and other stakeholders in filling gaps in (eco)toxicity data needed for assessing the hazards of chemicals. The development and release of the Toolbox is a cornerstone in the computerization of hazard assessment, providing an 'all inclusive' tool for the application of category approaches, such as read-across and trend analysis, in a single software application, free of charge. The Toolbox incorporates theoretical knowledge, experimental data and computational tools from various sources into a logical workflow. The main steps of this workflow are substance identification, identification of relevant structural characteristics and potential toxic mechanisms of interaction (i.e. profiling), identification of other chemicals that have the same structural characteristics and/or mechanism (i.e. building a category), data collection for the chemicals in the category and use of the existing experimental data to fill the data gap(s). The description of the Toolbox workflow and its main functionalities is the scope of the present article.
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Affiliation(s)
- S D Dimitrov
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - R Diderich
- b Organisation for Economic Co-operation and Development (OECD) , ENV/EHS, Paris , France
| | - T Sobanski
- c European Chemical Agency (ECHA) , Annankatu , Helsinki , Finland
| | - T S Pavlov
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - G V Chankov
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - A S Chapkanov
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - Y H Karakolev
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - S G Temelkov
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - R A Vasilev
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - K D Gerova
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - C D Kuseva
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - N D Todorova
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - A M Mehmed
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
| | - M Rasenberg
- c European Chemical Agency (ECHA) , Annankatu , Helsinki , Finland
| | - O G Mekenyan
- a Laboratory of Mathematical Chemistry , University 'Prof. As. Zlatarov' , Bourgas , Bulgaria
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