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Disentangling direct and indirect genetic effects from partners and offspring on maternal depression using trio-GCTA

Nature Mental Health volume 2, pages 417–425 (2024)Cite this article

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Abstract

Maternal depressive symptoms are highly prevalent and can negatively impact affected individuals and family members. Understanding etiological influences on maternal depression, such as genetic liability, is key to inform treatment and prevention efforts. Here we quantified direct and indirect genetic effects (that is, when genetic variants in other individuals influence risk of maternal depression through the environment) from partners and offspring on maternal depressive symptoms at multiple time points using genome-wide complex trait analysis with parent–offspring trios. We used data from the Norwegian Mother, Father and Child cohort study, including up to 21,000 genotyped parent–offspring trios. Models with indirect genetic effects had best fit at three out of five time points (3, 5 and 8 years after birth). The variance in maternal depressive symptoms explained by direct genetic effects ranged from 5% to 14%, whereas indirect genetic effects explained 0–14% of variance across time points. Heritable traits in family members contribute to maternal depressive symptoms through the environment at several time points after birth.

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Fig. 1: Conceptual model of mother-, partner- and child-driven effects on maternal depression.
Fig. 2: Estimates of direct and indirect genetic effects at separate time points.

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Data availability

MoBa data can be accessed by application to the Regional Committee for Medical and Health 494 Research Ethics in Norway and MoBa (https://www.fhi.no/en/ch/studies/moba/for-forskere-artikler/research-and-data-access/). The consent given by the participants does not open for storage of data on an individual level in repositories or journals.

Code availability

The code used in this study is available upon request from the first author. Example code for fitting variance-component models structured according to relationship matrices with VCModels.jl is provided at: https://github.com/espenmei/VCModels.jl.

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Acknowledgements

The Research Council of Norway supported R.C., R.B.N., E.R., and T.A.M. (288083); H.A. (274611); A.H. (274611, 336085); L.D.B. (314843) and E.Y. 288083, 262177, 336078, and 331640). The South-Eastern Norway Regional Health Authority supported L.J.H. (2022083 and 2018058) and A.H. (2020022). L.D.B. has received internationalization support from UiO:Life Science. J.R.B. is supported by a Sir Henry Wellcome Postdoctoral Fellowship (215917/Z/19/Z). The positions of T.A.M. and Y.I.A., were funded by a Wellcome Trust Senior Research Fellowship awarded to T.A.M. (220382/Z/20/Z). E.Y. is funded by the European Research Council under the Horizon 2020 (818425) and the Horizon Europa program (101045526). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

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  1. Espen Moen Eilertsen

    Present address: PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway

Authors and Affiliations

  1. PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway

    Ludvig Daae Bjørndal, Ziada Ayorech, Rosa Cheesman, Helga Ask, Tom A. McAdams, Alexandra Havdahl, Ragnhild Bang Nes, Espen Røysamb & Eivind Ystrom

  2. Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway

    Espen Moen Eilertsen

  3. Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK

    Yasmin I. Ahmadzadeh, Jessie R. Baldwin & Tom A. McAdams

  4. Department of Clinical, Educational and Health Psychology, University College London, London, UK

    Jessie R. Baldwin

  5. PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway

    Helga Ask, Laurie John Hannigan, Alexandra Havdahl & Eivind Ystrom

  6. Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway

    Laurie John Hannigan & Alexandra Havdahl

  7. Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK

    Laurie John Hannigan

  8. Department of Philosophy, Classics, and History of Arts and Ideas, University of Oslo, Oslo, Norway

    Ragnhild Bang Nes

  9. Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway

    Ragnhild Bang Nes & Espen Røysamb

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  1. Ludvig Daae Bjørndal
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Contributions

L.D.B., E.M.E. and E.Y. were responsible for the concept, design and analysis of data. L.D.B., E.M.E., Z.A., R.C., Y.I.A., J.R.B., H.A., L.J.H., T.A.M., A.H., R.B.N., E.R. and E.Y. contributed to the interpretation of the results. Drafting of the manuscript was done by L.D.B., while E.M.E., Z.A., R.C., Y.I.A., J.R.B., H.A., L.J.H., T.A.M., A.H., R.B.N., E.R. and E.Y. provided critical revision of the manuscript for important intellectual content.

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Correspondence to Ludvig Daae Bjørndal or Eivind Ystrom.

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Bjørndal, L.D., Eilertsen, E.M., Ayorech, Z. et al. Disentangling direct and indirect genetic effects from partners and offspring on maternal depression using trio-GCTA. Nat. Mental Health 2, 417–425 (2024). https://doi.org/10.1038/s44220-024-00207-3

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