| |  Online-Ressource |
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| Verfasst von: | Adams, Mark J. [VerfasserIn]  |
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| | Thorp, Jackson G. [VerfasserIn] |
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| | Jermy, Bradley S. [VerfasserIn] |
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| | Kwong, Alex S. F. [VerfasserIn] |
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| | Kõiv, Kadri [VerfasserIn] |
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| | Grotzinger, Andrew D. [VerfasserIn] |
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| | Nivard, Michel G. [VerfasserIn] |
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| | Marshall, Sally [VerfasserIn] |
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| | Milaneschi, Yuri [VerfasserIn] |
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| | Baune, Bernhard T. [VerfasserIn] |
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| | Müller-Myhsok, Bertram [VerfasserIn] |
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| | Penninx, Brenda W. J. H. [VerfasserIn] |
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| | Boomsma, Dorret I. [VerfasserIn] |
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| | Levinson, Douglas F. [VerfasserIn] |
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| | Breen, Gerome [VerfasserIn] |
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| | Pistis, Giorgio [VerfasserIn] |
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| | Grabe, Hans J. [VerfasserIn] |
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| | Tiemeier, Henning [VerfasserIn] |
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| | Berger, Klaus [VerfasserIn] |
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| | Rietschel, Marcella [VerfasserIn] |
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| | Magnusson, Patrik K. [VerfasserIn] |
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| | Uher, Rudolf [VerfasserIn] |
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| | Hamilton, Steven P. [VerfasserIn] |
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| | Lucae, Susanne [VerfasserIn] |
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| | Lehto, Kelli [VerfasserIn] |
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| | Li, Qingqin S. [VerfasserIn] |
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| | Byrne, Enda M. [VerfasserIn] |
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| | Hickie, Ian B. [VerfasserIn] |
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| | Martin, Nicholas G. [VerfasserIn] |
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| | Medland, Sarah E. [VerfasserIn] |
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| | Wray, Naomi R. [VerfasserIn] |
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| | Tucker-Drob, Elliot M. [VerfasserIn] |
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| | Team, Estonian Biobank Research [VerfasserIn] |
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| | Lewis, Cathryn M. [VerfasserIn] |
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| | McIntosh, Andrew M. [VerfasserIn] |
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| | Derks, Eske M. [VerfasserIn] |
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| Titel: | Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts |
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| Verf.angabe: | Mark J. Adams, Jackson G. Thorp, Bradley S. Jermy, Alex S.F. Kwong, Kadri Kõiv, Andrew D. Grotzinger, Michel G. Nivard, Sally Marshall, Yuri Milaneschi, Bernhard T. Baune, Bertram Müller-Myhsok, Brenda W.J.H. Penninx, Dorret I. Boomsma, Douglas F. Levinson, Gerome Breen, Giorgio Pistis, Hans J. Grabe, Henning Tiemeier, Klaus Berger, Marcella Rietschel, Patrik K. Magnusson, Rudolf Uher, Steven P. Hamilton, Susanne Lucae, Kelli Lehto, Qingqin S. Li, Enda M. Byrne, Ian B. Hickie, Nicholas G. Martin, Sarah E. Medland, Naomi R. Wray, Elliot M. Tucker-Drob, Estonian Biobank Research Team, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Cathryn M. Lewis, Andrew M McIntosh, and Eske M. Derks |
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| E-Jahr: | 2024 |
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| Jahr: | 26 September 2024 |
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| Umfang: | 10 S. |
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| Fussnoten: | Gesehen am 07.01.2025 |
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| Titel Quelle: | Enthalten in: Psychological medicine |
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| Ort Quelle: | Cambridge : Cambridge University Press, 1970 |
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| Jahr Quelle: | 2024 |
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| Band/Heft Quelle: | 54(2024), 12, Seite 3459-3468 |
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| ISSN Quelle: | 1469-8978 |
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| Abstract: | BackgroundDiagnostic 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.MethodsWe 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.ResultsThe 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).ConclusionThe 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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| DOI: | doi:10.1017/S0033291724001880 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
kostenfrei: Volltext: https://doi.org/10.1017/S0033291724001880 |
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| | kostenfrei: Volltext: http://www.cambridge.org/core/journals/psychological-medicine/article/genomewide-metaanalysis-of-ascertainment-and-sympt ... |
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| | DOI: https://doi.org/10.1017/S0033291724001880 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | depressive symptoms |
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| | genome-wide association study |
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| | Genomic SEM |
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| | major depressive disorder |
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| | psychometrics |
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| K10plus-PPN: | 1913637468 |
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| Verknüpfungen: | → Zeitschrift |
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Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts / Adams, Mark J. [VerfasserIn]; 26 September 2024 (Online-Ressource)
