Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts
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 informativ...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
26 September 2024
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| In: |
Psychological medicine
Year: 2024, Volume: 54, Issue: 12, Pages: 3459-3468 |
| ISSN: | 1469-8978 |
| DOI: | 10.1017/S0033291724001880 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1017/S0033291724001880 Verlag, kostenfrei, Volltext: http://www.cambridge.org/core/journals/psychological-medicine/article/genomewide-metaanalysis-of-ascertainment-and-symptom-structures-of-major-depression-in-caseenriched-and-community-cohorts/01FE9A359BB20151ECCF123BAC1B9CD3 
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| Author Notes: | 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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| 245 | 1 | 0 | |a Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts |c 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 |
| 264 | 1 | |c 26 September 2024 | |
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| 520 | |a 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. | ||
| 650 | 4 | |a depressive symptoms | |
| 650 | 4 | |a genome-wide association study | |
| 650 | 4 | |a Genomic SEM | |
| 650 | 4 | |a major depressive disorder | |
| 650 | 4 | |a psychometrics | |
| 700 | 1 | |a Thorp, Jackson G. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Jermy, Bradley S. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Kwong, Alex S. F. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Kõiv, Kadri |e VerfasserIn |4 aut | |
| 700 | 1 | |a Grotzinger, Andrew D. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Nivard, Michel G. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Marshall, Sally |e VerfasserIn |4 aut | |
| 700 | 1 | |a Milaneschi, Yuri |e VerfasserIn |4 aut | |
| 700 | 1 | |a Baune, Bernhard T. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Müller-Myhsok, Bertram |e VerfasserIn |4 aut | |
| 700 | 1 | |a Penninx, Brenda W. J. H. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Boomsma, Dorret I. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Levinson, Douglas F. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Breen, Gerome |e VerfasserIn |4 aut | |
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| 700 | 1 | |a Grabe, Hans J. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Tiemeier, Henning |e VerfasserIn |4 aut | |
| 700 | 1 | |a Berger, Klaus |e VerfasserIn |4 aut | |
| 700 | 1 | |a Rietschel, Marcella |d 1957- |e VerfasserIn |0 (DE-588)112785751 |0 (DE-627)505574020 |0 (DE-576)289742307 |4 aut | |
| 700 | 1 | |a Magnusson, Patrik K. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Uher, Rudolf |e VerfasserIn |4 aut | |
| 700 | 1 | |a Hamilton, Steven P. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Lucae, Susanne |e VerfasserIn |4 aut | |
| 700 | 1 | |a Lehto, Kelli |e VerfasserIn |4 aut | |
| 700 | 1 | |a Li, Qingqin S. |e VerfasserIn |4 aut | |
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| 700 | 1 | |a Team, Estonian Biobank Research |e VerfasserIn |4 aut | |
| 700 | 1 | |a Lewis, Cathryn M. |e VerfasserIn |4 aut | |
| 700 | 1 | |a McIntosh, Andrew M. |e VerfasserIn |4 aut | |
| 700 | 1 | |a Derks, Eske M. |e VerfasserIn |4 aut | |
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