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Infant subcortical brain volumes associated with maternal obesity and diabetes: a large multicohort human study

  • Ann M Alex
  • , Jerod M Rasmussen
  • , Jetro J Tuulari
  • , Julie Nihouarn Sigurdardottir
  • , Claudia Buss
  • , Kirsten A Donald
  • , A David Edwards
  • , Sonja Entringer
  • , John H Gilmore
  • , Nynke A Groenewold
  • , Hasse Karlsson
  • , Linnea Karlsson
  • , Katherine E Lawrence
  • , Inka Mattila
  • , Dan J Stein
  • , Martin Styner
  • , Paul M Thompson
  • , Pathik D Wadhwa
  • , Heather J Zar
  • , Xi Zhu
  • Gustavo de Los Campos, Rebecca C Knickmeyer, Shan Luo, ENIGMA-ORIGINs working group
  • College of Medicine
  • University of California, Irvine
  • University of Turku
  • Department of Early Life Imaging
  • School of Biomedical Engineering & Imaging Sciences
  • King's College London
  • Department of Forensic and Neurodevelopmental Sciences
  • Institute of Psychiatry and Neuroscience
  • University of Cape Town
  • School of Biomedical Engineering and Imaging Sciences
  • University of North Carolina at Chapel Hill
  • USC University of Southern California
  • University of Texas at Arlington
  • Michigan State University

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Maternal diabetes and obesity are established risk factors for adverse offspring health. Emerging evidence suggests that these fetal programming effects vary by sex, yet it remains unclear whether these factors independently or interactively influence early brain development. Methods: This prospective study included 1,965 infants from six international cohorts. Infant MRI was used to derive subcortical volumes (thalamus, amygdala, hippocampus, pallidum, putamen, caudate). ComBat harmonization was applied. Multiple linear regression tested main and interaction effects of maternal obesity, maternal diabetes, and sex, controlling for covariates with false discovery rate (FDR) corrections. Results: Of the sample, 46% were female (N = 909), 9% were exposed to maternal diabetes (N = 172), 22% to maternal obesity (N = 386), and 3% to both (N = 61). MRI scans were performed at 25.9 ± 18.8 days. Maternal diabetes was associated with smaller thalamic volume (standardized β = -0.09, 95%CI –0.16 to -0.01, FDR P = 0.020), but this association was attenuated after adjusting for maternal obesity. Maternal obesity was associated with smaller hippocampal (standardized β = -0.13, 95%CI -0.21 to –0.05, FDR P = 0.009) and thalamic volumes (standardized β = -0.09, 95%CI -0.14 to –0.03, FDR P = 0.007). Sex-specific associations were observed. In females, maternal obesity was associated with smaller hippocampal (standardized β = -0.24, 95%CI -0.36 to -0.13, FDR P < 0.001) and amygdala volumes (standardized β = -0.18, 95% CI = -0.30 to –0.06, FDR P = 0.016). A three-way interaction (diabetes x obesity x sex) was observed for thalamus volume (standardized β = -0.50, 95%CI -0.81 to -0.18, FDR P = 0.017). In males, combined exposure had lower thalamic volume compared to those with one or neither exposure (all Ps < 0.05). In females, maternal obesity (standardized β = -0.12, 95%CI -0.20 to –0.04, FDR P = 0.015) and diabetes (standardized β = -0.16, 95%CI -0.30 to –0.02, FDR P = 0.042) showed independent associations with thalamic volume, without a significant interaction (standardized β = 0.23, 95%CI -0.01 to 0.46, FDR P = 0.092). Conclusions: Maternal obesity shows stronger associations with infant subcortical volumes than maternal diabetes. It is associated with smaller hippocampal and amygdala volumes in females, while combined exposure to maternal diabetes and obesity is associated with smaller thalamic volumes in males. These findings highlight the role of maternal metabolic health and infant sex in early neurodevelopment.

Original languageEnglish
Article number327
JournalBMC Medicine
Volume24
Issue number1
Early online date16 Apr 2026
DOIs
Publication statusE-pub ahead of print - 16 Apr 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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