Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness

  1. van Houtum, Lisanne A. E. M.
  2. Baaré, William F. C.
  3. Beckmann, Christian F.
  4. Castro-Fornieles, Josefina
  5. Cecil, Charlotte A. M.
  6. Dittrich, Juliane
  7. H. Ebdrup, Björn
  8. Fegert, Jörg M.
  9. Havdahl, Alexandra
  10. Hillegers, Manon H. J.
  11. Kalisch, Raffael
  12. Kushner, Steven A.
  13. Mansuy, Isabelle M.
  14. Mežinska, Signe
  15. Moreno, Carmen
  16. Muetzel, Ryan L.
  17. Neumann, Alexander
  18. Nordentoft, Merete
  19. Pingault, Jean-Baptiste
  20. Preisig, Martin
  21. Raballo, Andrea
  22. Saunders, John
  23. Sprooten, Emma
  24. Sugranyes, Gisela
  25. Tiemeier, Henning
  26. van Woerden, Geeske M.
  27. Vandeleur, Caroline L.
  28. van Haren, Neeltje E. M.

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1000 Titel
  • Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness
1000 Autor/in
  1. van Houtum, Lisanne A. E. M. |
  2. Baaré, William F. C. |
  3. Beckmann, Christian F. |
  4. Castro-Fornieles, Josefina |
  5. Cecil, Charlotte A. M. |
  6. Dittrich, Juliane |
  7. H. Ebdrup, Björn |
  8. Fegert, Jörg M. |
  9. Havdahl, Alexandra |
  10. Hillegers, Manon H. J. |
  11. Kalisch, Raffael |
  12. Kushner, Steven A. |
  13. Mansuy, Isabelle M. |
  14. Mežinska, Signe |
  15. Moreno, Carmen |
  16. Muetzel, Ryan L. |
  17. Neumann, Alexander |
  18. Nordentoft, Merete |
  19. Pingault, Jean-Baptiste |
  20. Preisig, Martin |
  21. Raballo, Andrea |
  22. Saunders, John |
  23. Sprooten, Emma |
  24. Sugranyes, Gisela |
  25. Tiemeier, Henning |
  26. van Woerden, Geeske M. |
  27. Vandeleur, Caroline L. |
  28. van Haren, Neeltje E. M. |
1000 Erscheinungsjahr 2024
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-04-13
1000 Erschienen in
1000 Quellenangabe
  • 33(11):3885-3898
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s00787-024-02423-9 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11588957/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one’s children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.
1000 Sacherschließung
lokal Family
lokal Offspring
lokal Resilience
lokal Intergenerational transmission
lokal Mental illness
lokal Risk prediction
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
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