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Pregnancy leads to long-lasting changes in human brain structure

Nature Neuroscience volume 20, pages 287–296 (2017)Cite this article

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Abstract

Pregnancy involves radical hormone surges and biological adaptations. However, the effects of pregnancy on the human brain are virtually unknown. Here we show, using a prospective ('pre'-'post' pregnancy) study involving first-time mothers and fathers and nulliparous control groups, that pregnancy renders substantial changes in brain structure, primarily reductions in gray matter (GM) volume in regions subserving social cognition. The changes were selective for the mothers and highly consistent, correctly classifying all women as having undergone pregnancy or not in-between sessions. Interestingly, the volume reductions showed a substantial overlap with brain regions responding to the women's babies postpartum. Furthermore, the GM volume changes of pregnancy predicted measures of postpartum maternal attachment, suggestive of an adaptive process serving the transition into motherhood. Another follow-up session showed that the GM reductions endured for at least 2 years post-pregnancy. Our data provide the first evidence that pregnancy confers long-lasting changes in a woman's brain.

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Figure 1: GM volume changes between pre-pregnancy and post-pregnancy session.
Figure 2: Means of conception.
Figure 3: Classification.
Figure 4: Similarity between theory-of-mind network and GM volume changes of pregnancy.
Figure 5: Surface-based measures.
Figure 6: Postpartum infant-related neural activity and attachment scores.
Figure 7: Long-term follow-up.

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Acknowledgements

We acknowledge the participants for their contribution to this study. We thank A. Bulbena for supporting the project, and M. López, G. Pons, R. Martínez, L. González, E. Castaño, N. Mallorquí-Bagué, J. Fauquet and C. Pretus for helping with the data collection and scoring of the cognitive tests. In addition, we thank C. Phillips and J.D. Gispert for advice on the multivariate analyses, E. Marinetto and C. Falcón for advice on the FreeSurfer analyses, and J. van Hemmen and J. Bakker for discussions of the project and results. E.H. was supported by a Formación de Profesorado Universitario (FPU) grant by the Ministerio de Educación y Ciencia, Spanish government, and is now supported by an Innovational Research Incentives Scheme grant (Veni, 451-14-036) of the Netherlands Organization for Scientific Research (NWO), E.B.-M. by a grant from the National Council of Science and Technology of Mexico, S.C. by the Consejería de Educación, Juventud y Deporte of Comunidad de Madrid and the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement 291820, and M.P. by an FI grant of the Agencia de Gestió d'Ajuts Universitaris de Recerca, Generalitat de Catalunya.

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Author notes

  1. Elseline Hoekzema and Erika Barba-Müller: These authors contributed equally to this work.

  2. Susanna Carmona and Oscar Vilarroya: These authors jointly supervised this work.

Authors and Affiliations

  1. Unitat de Recerca en Neurociència Cognitiva, Departament de Psiquiatria i Medicina Legal, Universitat Autònoma de Barcelona, Barcelona, Spain

    Elseline Hoekzema, Erika Barba-Müller, Marisol Picado, Juan Carlos Soliva, Adolf Tobeña, Susanna Carmona & Oscar Vilarroya

  2. Brain and Development Laboratory, Leiden University, Leiden, the Netherlands

    Elseline Hoekzema & Eveline A Crone

  3. Leiden Institute for Brain and Cognition (LIBC), Leiden University, Leiden, the Netherlands

    Elseline Hoekzema & Eveline A Crone

  4. Instituto Valenciano de Infertilidad, Barcelona, Spain

    Cristina Pozzobon, Florencio Lucco & Agustín Ballesteros

  5. Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain

    David García-García, Manuel Desco & Susanna Carmona

  6. Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain

    Susanna Carmona

  7. Fundació IMIM, Barcelona, Spain

    Oscar Vilarroya

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  1. Elseline Hoekzema
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Contributions

E.H., E.B.-M., S.C., and O.V. designed the experiments. C.P., A.B., and F.L. recruited part of the participants and provided clinical information. E.B.-M. oversaw the overall timeline, recruitment and data collection of the project, and acquired the data together with E.H., M.P. and S.C. J.C.S., A.T., M.D., E.A.C. and O.V. provided facilities and advice on aspects of design, acquisition or interpretation. E.H. analyzed the data, except for the area and thickness analysis done by S.C. and D.G.-G. E.H. wrote the manuscript and all other authors evaluated and approved the manuscript.

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Correspondence to Elseline Hoekzema.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Plots of the remaining clusters

For the remaining clusters not indicated in the main figures (the left inferior orbitofrontal and the left middle frontal cluster, see Table 1), this figure depicts the (a) slice overlays,(b) plots representing the mean signal from the smoothed normalized jacobian difference images of the PRE and POST session, and (c) plots representing the mean (M±S.E.M.) signal change at each POST session relative to the pre-pregnancy baseline. FCTR=nulliparous control women, FPRG=women who were pregnant and transitioned into primiparity in-between sessions, Inf.= Inferior, Mid.= Middle, L=Left.

Supplementary Figure 2 Effect sizes

(a) Illustration of the effect sizes (Cohen's d) for the changes in GM volume in the women who were pregnant in-between sessions in comparison to the control women. All depicted effect sizes correspond to large effect sizes (Cohen's d>0.8), although it should be noted that effect sizes from mapping experiments can be optimistically biased. Effect sizes were additionally computed separately for the GM volume changes in women achieving pregnancy by means of natural conception (b), and the women achieving pregnancy by fertility treatment (c). Yellow/orange tones correspond to reductions in GM volume across sessions in primiparous women in comparison to nulliparous control women, while blue tones represent relative increases in primiparous women in comparison to the control group. Effect sizes were extracted using the VBM8 toolbox (http://www.neuro.uni-jena.de/vbm/) and plotted in CARET (http://brainvis.wustl.edu).

Supplementary Figure 3 Pituitary gland volume

Bar charts (a) and scatter plots (b) depicting pituitary gland volume in each session. The pituitary gland was manually delineated as a complementary analysis to further explore the data based on the previous findings of larger pituitary volume in pregnant women. Mean pituitary gland volume was about 40 mm3 larger in the early postpartum session than in the PRE and the POST+2yrs sessions (M±SD: PRE: 622.80±91.47 mm3. POST: 663±58-93.36 mm3. POST+2yrs: 626.07±93.85 mm3), although this PRE-to-POST increase is not significant (GLM repeated measures: F=1.50, p=0.235). Accordingly, the observed increase of 7% in the POST session is subtle compared to the relative volume increases previously observed in late pregnancy, which fits with previous findings showing that the pituitary gland rapidly loses most of its volume gains shortly after birth. A significant reduction was observed between the early postpartum and the POST+2yrs session (F=21.32, p=0.001), suggesting that pituitary volumes in the POST session had not yet completely returned to pre-pregnancy levels yet. As expected, pituitary gland volume at the POST+2yrs session did not differ from the pre-pregnancy baseline (F=0.002, p=0.968).

Supplementary Figure 4 Individual GM volume changes separated by means of conception

Plots representing mean signal from the smoothed normalized jacobian difference images averaged across cluster for the women achieving pregnancy by fertility treatment (FTRT, N=16), women achieving pregnancy by natural conception (FNAT, N=9) and nulliparous control women who were not pregnant in-between sessions (FCTR, N=20). Sup. Temp. Sulcus = Superior Temporal Sulcus, Med.= Medial, Inf.= Inferior, Mid.= Middle, L=left, R=right.

Supplementary Figure 5 Surface-projected weight maps for multivariate classification

Projections of the average weight map, illustrating the relative importance of each voxel in the decision function, for the support vector machine classification results (see main manuscript) onto the brain's surface.

Supplementary Figure 6 Individual GM volume changes per cluster for all four groups

Plots representing mean signal from the smoothed normalized jacobian difference images for each group averaged across cluster. FCTR=nulliparous control women, FPRG= women who were pregnant and became first-time mothers in-between sessions. MCTR=nulliparous control men whose partners were not pregnant in-between sessions, MPRG= men whose partners were pregnant and who became first-time fathers in-between sessions, Sup. Temp. Sulcus = Superior Temporal Sulcus, Med.= Medial, Inf.= Inferior, Mid.= Middle, L=left, R=right.

Supplementary Figure 7 Weight maps for multivariate regression results

Slice overlays depicting the average weight map, illustrating the relative importance of each voxel in the multivariate regression, for the kernel ridge regression analyses (see main manuscript). (a) Absence of hostility. (b) Quality of attachment.

Supplementary Figure 8 Surface-projected weight maps for multivariate regression results

Projections of the average weight map, illustrating the relative importance of each voxel in the multivariate regression, for the kernel ridge regression analyses (see main manuscript) onto the brain's surface. (a) Absence of hostility. (b) Quality of attachment.

Supplementary Figure 9 Overlap structural changes and postpartum fMRI results

Slice overlays depicting the overlap between the changes in GM volume across pregnancy and the ‘own baby>other baby' contrast of the postpartum fMRI paradigm. A red color indicates the area was present in both maps, while light and dark blue depict areas that were only present in either the structural or the fMRI map respectively.

Supplementary Figure 10 Pre and Post plots

Illustration of GM signal in the PRE and POST sessions for the group of women who were pregnant in-between sessions and those who were not. Images were processed using a cross-sectional voxel-based morphometry approach. Due to the large inter-individual variability in GM values, the groups could not clearly be separated from one another visually when plotted in scatterplots, stressing the importance of using a pre-pregnancy baseline to map changes on an individual level. Therefore, bar charts depicting the group means (M±SEM) are provided for each of the regions. FCTR=nulliparous control women, FPRG=women who were pregnant and transitioned into primiparity in-between sessions, Sup. Temp. Sulcus = Superior Temporal Sulcus, Med.= Medial, Inf.= Inferior, Mid.= Middle, L=left, R=right.

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Supplementary Figures 1–10 and Supplementary Tables 1–23 (PDF 2481 kb)

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Hoekzema, E., Barba-Müller, E., Pozzobon, C. et al. Pregnancy leads to long-lasting changes in human brain structure. Nat Neurosci 20, 287–296 (2017). https://doi.org/10.1038/nn.4458

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