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Neonatal amygdala microstructure and structural connectivity are associated with autistic traits at 2 years of age.

Overview

Authors: Kadi Vaher1,2, Samuel R. Neal1, Manuel Blesa Cábez1,2, Lorena Jiménez-Sánchez2,3, Amy Corrigan1, David Q. Stoye1, Helen L. Turner2,4, Rebekah Smikle1, Hilary Cruickshank4, Magda Rudnicka4, Mark E. Bastin2, Michael J. Thrippleton2, Rebecca M. Reynolds1,5, James P. Boardman1,2
ORCID iDs: Kadi Vaher, Samuel R. Neal, James P. Boardman
  1. Centre for Reproductive Health, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh, UK
  2. Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
  3. Salvesen Mindroom Research Centre, The University of Edinburgh, Edinburgh, UK
  4. Simpson Centre for Reproductive Health, Royal Infirmary Edinburgh, Edinburgh, United Kingdom
  5. Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
Institutions: MRC Centre for Reproductive Health (United Kingdom); University of Edinburgh (United Kingdom); Edinburgh Royal Infirmary (United Kingdom)
Journal: Developmental cognitive neuroscience, volume 79, article 101721
Dates: received 13 February 2025; accepted 6 April 2026; published online 7 April 2026; in print June 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1016/j.dcn.2026.101721 · PMID 41955686 · PMCID PMC13091228 · OpenAlex W4404937202
Open access: gold, a free copy (OpenAlex)
Preprint: doi:10.1101/2024.11.29.24318196
Status: code verified
Categories: structural MRI / diffusion (modality), human (organism), autism (population), developmental (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions, Connectivity, fMRI & imaging
Keywords: Amygdala, Diffusion MRI, Q-CHAT, Autistic traits, Network-based statistics, Cortisol
MeSH: Amygdala*, Autistic Disorder*, Child, Preschool, Female, Humans, Infant, Newborn, Magnetic Resonance Imaging, Male, Neural Pathways, Neurodevelopment (* major topic)
Topic: Autism Spectrum Disorder Research (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Wellcome (108890/Z/15/Z, 218493/Z/19/Z], 108890/Z/15/Z), 218493/Z/19/Z); RCUK | Medical Research Council (MRC) (MR/X003434/1); Dunhill Medical Trust; Edinburgh and Lothians Research Foundation; Theirworld; Muir Maxwell Trust; Simpson Special Care Babies charity
Citations: cited by 1 paper (Europe PMC); 106 references in the paper

Abstract

Prenatal maternal stress is linked to neurodevelopmental outcomes. Maternal hair cortisol concentration in pregnancy is associated with neonatal amygdala microstructure and structural connectivity, suggesting that amygdala is sensitive to antenatal stress. We investigated whether amygdala microstructure and/or connectivity associate with neurodevelopmental outcomes. 174 participants (105 preterm) underwent brain MRI at term-equivalent age and assessment of neurodevelopment, autistic traits, temperament, and executive function at 2 years corrected age. We calculated amygdala microstructure (fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index) and structural connectivity (mean fractional anisotropy) to 6 regions (insula, putamen, thalamus, inferior temporal gyrus, medial orbitofrontal cortex, rostral anterior cingulate cortex). We used linear regression to model amygdala-outcome associations, adjusting for gestational age at birth and at scan, sex, maternal education and postnatal depression score, and network-based statistics (NBS) for whole-brain analyses. Following correction for multiple comparisons, lower amygdala mean diffusivity (left: β = -0.32, p = 0.026, right: β = -0.38, p = 0.012), higher left amygdala neurite density index (β = 0.35, p = 0.026), and increased left amygdala-putamen connectivity (β = 0.31, p = 0.026) associated with higher autistic traits across the whole sample. NBS additionally revealed amygdala-involving networks associated with cognition and surgency among preterms, and gestation-dependent associations with autistic traits. Findings indicate that neonatal amygdala microstructure may be important in the development of autistic traits.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

No file of the authors' code could be read here: it is described below, and read at its source.

git.ecdf.ed.ac.uk/jbrl/amy-neurodev

License: none: the authors keep all their rights
State: the link answers, verified on 29 September 2026
Evidence: the link answers
Software Heritage: not checked
Found in: “Data and code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 29 September 2026: the link answers (HTTP 200)
  • 29 September 2026: the link answers (HTTP 200)
At the source: git.ecdf.ed.ac.uk/jbrl/amy-neurodev

The paper's code and data availability statement is in the Data section.

Tracing map

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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data Availability

Data access process and analysis code repository are detailed in section 2.6 Data and code availability.

Reproduced under the paper's license (CC BY), from the paper cited above.

Data and code availability

Data used for analysis in this work are deposited in Edinburgh DataVault (Boardman et al. 2022) (https://doi.org/10.7488/e65499db-2263–4d3c-9335–55ae6d49af2b (https://doi.org/10.7488/e65499db-2263-4d3c-9335-55ae6d49af2b)). Requests for access for these as well as raw neuroimaging data will be considered under the study's Data Access and Collaboration policy and governance process (https://www.ed.ac.uk/centre-reproductive-health/tebc/about-tebc/for-researchers/data-access-collaboration, ). Code used for the data analysis in this paper is available on GitLab (https://git.ecdf.ed.ac.uk/jbrl/amy-neurodev).

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 14 authors, 6 keywords, 10 MeSH terms, 7 funders, 102 references.

Cite

This paper

Vaher, K., Neal, S. R., Cábez, M. B., Jiménez-Sánchez, L., Corrigan, A., Stoye, D. Q., Turner, H. L., Smikle, R., Cruickshank, H., Rudnicka, M., Bastin, M. E., Thrippleton, M. J., Reynolds, R. M., & Boardman, J. P. (2026). Neonatal amygdala microstructure and structural connectivity are associated with autistic traits at 2 years of age. Developmental cognitive neuroscience, 79, 101721. https://doi.org/10.1016/j.dcn.2026.101721

BibTeX

@article{vaher2026neonatal,
author = {Vaher, Kadi and Neal, Samuel R. and Cábez, Manuel Blesa and Jiménez-Sánchez, Lorena and Corrigan, Amy and Stoye, David Q. and Turner, Helen L. and Smikle, Rebekah and Cruickshank, Hilary and Rudnicka, Magda and Bastin, Mark E. and Thrippleton, Michael J. and Reynolds, Rebecca M. and Boardman, James P.},
title = {{Neonatal amygdala microstructure and structural connectivity are associated with autistic traits at 2 years of age}},
journal = {Developmental cognitive neuroscience},
year = {2026},
month = apr,
volume = {79},
pages = {101721},
publisher = {Elsevier},
issn = {1878-9293},
doi = {10.1016/j.dcn.2026.101721},
url = {https://doi.org/10.1016/j.dcn.2026.101721},
pmid = {41955686},
pmcid = {PMC13091228}
}

RIS

TY - JOUR
AU - Vaher, Kadi
AU - Neal, Samuel R.
AU - Cábez, Manuel Blesa
AU - Jiménez-Sánchez, Lorena
AU - Corrigan, Amy
AU - Stoye, David Q.
AU - Turner, Helen L.
AU - Smikle, Rebekah
AU - Cruickshank, Hilary
AU - Rudnicka, Magda
AU - Bastin, Mark E.
AU - Thrippleton, Michael J.
AU - Reynolds, Rebecca M.
AU - Boardman, James P.
TI - Neonatal amygdala microstructure and structural connectivity are associated with autistic traits at 2 years of age
T2 - Developmental cognitive neuroscience
J2 - Dev Cogn Neurosci
PY - 2026
DA - 2026/04/07
VL - 79
SP - 101721
SN - 1878-9293
PB - Elsevier
DO - 10.1016/j.dcn.2026.101721
UR - https://doi.org/10.1016/j.dcn.2026.101721
LA - en
ER -

CSL-JSON

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