1. Neuroscience

Maternal cortisol is associated with neonatal amygdala microstructure and connectivity in a sexually dimorphic manner

  1. David Q Stoye
  2. Manuel Blesa
  3. Gemma Sullivan
  4. Paola Galdi
  5. Gillian J Lamb
  6. Gill S Black
  7. Alan J Quigley
  8. Michael J Thrippleton
  9. Mark E Bastin
  10. Rebecca M Reynolds
  11. James P Boardman  Is a corresponding author
  1. MRC Centre for Reproductive Health, University of Edinburgh, United Kingdom
  2. Department of Radiology, Royal Hospital for Sick Children, United Kingdom
  3. Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom
  4. Centre for Cardiovascular Science, University of Edinburgh, United Kingdom
https://doi.org/10.7554/eLife.60729
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  1. David Q Stoye
  2. Manuel Blesa
  3. Gemma Sullivan
  4. Paola Galdi
  5. Gillian J Lamb
  6. Gill S Black
  7. Alan J Quigley
  8. Michael J Thrippleton
  9. Mark E Bastin
  10. Rebecca M Reynolds
  11. James P Boardman
(2020)
Maternal cortisol is associated with neonatal amygdala microstructure and connectivity in a sexually dimorphic manner
eLife 9:e60729.
https://doi.org/10.7554/eLife.60729
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4 figures, 4 tables and 5 additional files

Figures

Figure 1
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Partial regression plots of HCC and (A) left amygdala FA, (B) left amygdala ODI and (C) FA of connections between the right amygdala and putamen.

Plots are residualised for GA at birth, GA at scan, birthweight z-score and SIMD quintile. Boys are shown in blue, and girls in orange, along with the 95% confidence intervals.

Figure 1—source data 1

Demographic and information and image metrics.

https://cdn.elifesciences.org/articles/60729/elife-60729-fig1-data1-v1.xlsx
Figure 2 with 1 supplement
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Segmentations of the amygdalae and connected regions defined by the top 20% streamline counts.

Figure 1a shows the lateral view of the sagittal plane and 1b the medial view. The same eight regions had the highest streamline counts to the amygdalae bilaterally.

Figure 2—figure supplement 1
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Example segmentations of the amygdala in native space.

Right and left amygdala segmentations from a preterm infant at term equivalent age (upper row) and an infant born at term (lower row), viewed in native space.

Figure 3
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Chord diagram of the streamline counts between the amygdalae and unilateral regions of interest (ROIs).

The number of streamlines between ROIs are demonstrated by the corresponding arcs thickness. ROIs connected by the top 20% of streamlines are shown in green.

Author response image 1
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Pearson’s correlations between amygdala microstructural and the putamen to amygdala connectivity, in boys at the bottom left and girls at the top right.

Tables

Table 1
Maternal and neonatal characteristics.
Maternal characteristics, n = 71
Age (years)33.1 ± 5.2
BMI (kg/m2)25.2 ± 4.2
Primiparous (%)
Multiparous (%)		41 (58%)
30 (42%)
SIMD 2016 quintile n (%)*
1
2
3
4
5
4 (6%)
14 (20%)
10 (14%)
14 (20%)
29 (41%)
Tobacco smoked during pregnancy, n (%)
No tobacco smoked during pregnancy, n (%)		5 (7%)
66 (93%)
Gestational diabetes (%)
Preeclampsia (%)
Receiving pharmacological treatment for depression		1 (1%)
4 (6%)
3 (4%)
Infant characteristics, n = 78
Birthweight (g)2895 (454–4248)
Birth weight z-score†0.2 ± 1.1
Birth gestation (weeks)38.4 (24.0–42.0)
Male n (%)
Female		44 (56%)
34 (44%)
European ancestry n (%)
Other		68 (87%)
10 (13%)
Singleton n (%)
Twin		63 (81%)
15 (19%)

  1. Normally distributed data is presented as mean ± SD. Non-normally distributed data is presented as median (range).

    *Scottish Index of Multiple Deprivation (SIMD) 2016 quintile. First quintile indicates most deprived and fifth quintile the least deprived.

  2. †Calculated according to INTERGROWTH-21st standards.

Table 2
Associations of maternal hair cortisol concentration (HCC) and its interaction with infant sex on amygdala microstructure.
Model 1Model 2Model 3
Side testedImage metricR2R2HCC βHCC p-valueR2‘HCC x sex’ β‘HCC x sex’ p-value
LeftFA0.2670.269−0.0480.8580.3590.6770.010
MD0.4050.4050.0180.8580.413−0.1910.358
ODI0.1050.1110.0820.8580.181−0.5970.034
NDI0.5300.534−0.0640.8580.5610.3750.052
RightFA0.2890.308−0.1480.2690.3420.4150.083
MD0.4920.5230.1890.1430.530−0.1830.326
ODI0.2140.2280.1280.2690.283−0.5270.083
NDI0.5540.562−0.0940.2690.5830.3300.083

  1. Model 1: Age at MRI, gestational age at birth, birth weight z-score, Scottish Index of Multiple Deprivation 2016 quintile, infant sex. Model 2: Model 1 + (maternal HCC). Model 3: Model 2 + (maternal HCC x infant sex interaction). p-values are FDR adjusted. FA, fractional anisotropy; MD, mean diffusivity; ODI, orientation dispersion index; NDI, neurite density index; HCC, hair cortisol concentration, R2, coefficient of determination; β, standardised beta coefficient; p-value, FDR adjusted probability value.

Table 3
Associations of maternal hair cortisol concentration (HCC) with amygdala microstructural parameters assessed separately in boys and girls.
BoysGirls
Model 1Model 2Model 1Model 2
Side testedImage metricR2R2HCC βHCC p-valueR2R2HCC βHCC p-value
LeftFA0.4330.537−0.3390.0230.1570.2390.3400.372
MD0.4890.4970.0900.4620.4450.449−0.0720.667
ODI0.1240.2150.3170.0850.1320.159−0.1940.648
NDI0.6220.654−0.1890.0890.5220.5300.1090.648
RightFA0.3680.443−0.2870.0470.3010.3060.0910.736
MD0.5080.5710.2640.0470.4970.5060.1110.736
ODI0.1490.2360.3090.0470.3620.378−0.1490.736
NDI0.5810.623−0.2150.0470.5710.5730.0500.736

  1. Model 1: Gestational age at MRI, gestational age at birth, birth weight z-score, Scottish Index of Multiple Deprivation 2016 quintile. Model 2: Model 1 + (maternal HCC). p-values are FDR adjusted. FA, fractional anisotropy; MD, mean diffusivity; ODI, orientation dispersion index; NDI, neurite density index; HCC, hair cortisol concentration; R2, coefficient of determination; β, standardised beta coefficient; p-value, FDR adjusted probability value.

Key resources table
Reagent type
(species) or
resource		DesignationSource or
reference		IdentifiersAdditional
information
Software, algorithmMarchenko-
Pastur-PCA-based algorithm		PMID:27523449See Materials and methods, section Image Pre-processing
Software, algorithmMinimal processing
pipeline of the developing human connectome project (dHCP)		PMID:29409960See Materials and methods, section Image Pre-processing
Software, algorithmEddy current, head movement and EPI geometric distortions correction with outlier replacement and slice-to-volume registrationDW-MRI registration in FSLRRID:SCR_009461See Materials and methods, section Image Pre-processing
Software, algorithmBias field inhomogeneity correctionPMID:20378467See Materials and methods, section Image Pre-processing
Software, algorithmBoundary-based registrationPMID:19573611See Materials and methods, section Image Pre-processing
Software, algorithmAffine and symmetric normalisation (SyN) part of ANTS - Advanced Normalisation ToolSPMID:17659998RRID:SCR_004757105105105See Materials and methods, section Tissue Segmentation and Parcellation
Software, algorithmJoint label fusionPMID:22732662See Materials and methods, section Tissue Segmentation and Parcellation
Software, algorithmNODDINODDI Matlab ToolboxRRID:SCR_006826See Materials and methods, section Microstructure and volumetric assessments
Software, algorithmConstrained spherical deconvolution (CSD); MRtrixPMID:31473352RRID:SCR_006971See Materials and methods, section Network Construction Analysis
Software, algorithm• Anatomically-constrained tractography (ACT)PMID:22705374See Materials and methods, section Network Construction Analysis
Software, algorithmFiber orientation distribution (FOD)PMID:25109526See Materials and methods, section Network Construction Analysis
Software, algorithmSpherical-deconvolution informed filtering of tractograms twoPMID:26163802See Materials and methods, section Network Construction Analysis
Software, algorithmSPSSSPSSRRID:SCR_002865
Software, algorithmSeabornPython data visualisation library https://seaborn.pydata.org/ http://doi.org/10.5281/zenodo.883859RRID:SCR_018132Figure 1
Software, algorithmParaViewParaViewRRID:SCR_002516Figure 2
Software, algorithmITK-SNAPITK-SNAPRRID:SCR_002010Figure 2
Software, algorithmCircosCircosRRID:SCR_011798Figure 3
OtherLiquid chromatography-tandem mass spectrometry (LC-MS/MS)PMID:23584040See Materials and methods, section Maternal hair cortisol concentrations (HCC)

Additional files

Supplementary file 1

Univariate analysis of potential covariates with left and right amygdala volume and microstructure.

https://cdn.elifesciences.org/articles/60729/elife-60729-supp1-v1.xlsx
Supplementary file 2

Streamline counts between amygdalae and atlas regions.

https://cdn.elifesciences.org/articles/60729/elife-60729-supp2-v1.xlsx
Supplementary file 3

Associations of maternal hair cortisol concentration (HCC) and its interaction with offspring sex on mean fractional anisotropy (FA) of amygdala networks with high streamline count.

(a) Association between maternal hair cortisol concentration (HCC) and fractional anisotropy (FA) weighted connections of the amygdalae in boys and girls (b) Associations of maternal hair cortisol concentration (HCC) and its interaction with infant sex on amygdalae volume (c) Sensitivity and subgroup analyses assessing hair cortisol concentration (HCC) and infant sex interactions (d) Pearson’s correlations between perinatal exposures and amygdala volume, microstructure and connectivity.

https://cdn.elifesciences.org/articles/60729/elife-60729-supp3-v1.xlsx
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https://cdn.elifesciences.org/articles/60729/elife-60729-transrepform-v1.pdf
Reporting standard 1

STROBE Checklist for Observational Studies.

https://cdn.elifesciences.org/articles/60729/elife-60729-repstand1-v1.pdf.zip

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  1. David Q Stoye
  2. Manuel Blesa
  3. Gemma Sullivan
  4. Paola Galdi
  5. Gillian J Lamb
  6. Gill S Black
  7. Alan J Quigley
  8. Michael J Thrippleton
  9. Mark E Bastin
  10. Rebecca M Reynolds
  11. James P Boardman
(2020)
Maternal cortisol is associated with neonatal amygdala microstructure and connectivity in a sexually dimorphic manner
eLife 9:e60729.
https://doi.org/10.7554/eLife.60729