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. 2025;3(7):780-788.
doi: 10.1038/s44220-025-00447-x. Epub 2025 Jun 24.

Neuroimaging insights into brain mechanisms of early-onset restrictive eating disorders

Clara A Moreau  1 , Anael Ayrolles  2   3 , Christopher R K Ching  4 , Robin Bonicel  2   3 , Alexandre Mathieu  2 , Coline Stordeur  3 , Clara El Khantour  1 , Pierre Bergeret  1 , Nicolas Traut  5 , Lydie Tran  2 , David Germanaud  6   7   8 , Marianne Alison  9 , Monique Elmaleh-Bergès  9 , Stefan Ehrlich  10 , Paul M Thompson  4 , Thomas Bourgeron  2 , Richard Delorme  2   3
Affiliations

Neuroimaging insights into brain mechanisms of early-onset restrictive eating disorders

Clara A Moreau et al. Nat Ment Health. 2025.

Abstract

Early-onset restrictive eating disorders (rEO-ED) encompass a heterogeneous group of conditions, including early-onset anorexia nervosa (EO-AN) and avoidant/restrictive food intake disorders (ARFID). However, the impact of rEO-ED on brain morphometry remains largely unknown. Here we performed the largest magnetic resonance imaging-derived brain features comparison of children and early adolescents (<13 years) with EO-AN (n = 124) or ARFID (n = 50) versus typically developing individuals (TD, n = 116). EO-AN was associated with widespread cortex thinning, while underweight patients with ARFID exhibited reduced surface area and volumes compared with TD. Despite similar body mass index distributions, EO-AN and ARFID showed distinct structural patterns, suggesting independent brain mechanisms. Finally, we identified overlapping patterns of brain thickness differences between EO-AN and obsessive-compulsive disorder and between ARFID and autism spectrum disorder. Future studies are required to partition the contribution of body mass index versus rEO-ED mechanisms, as well as to identify shared mechanisms with other neurodevelopmental conditions toward a multidimensional approach of eating disorders.

Keywords: Brain; Diagnostic markers; Feeding behaviour.

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Conflict of interest statement

Competing interestsThe authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Characterization of the effect of rEO-EDs on brain structure.
a, The effect of EO-AN (dark red dots, n = 124) and ARFID (yellow dots, n = 50) compared with TD (n = 116) on five global brain metrics (ICV, total SA, mean CT, CSF and total GV). The triangles represent significant effect sizes. Data are presented as mean values ±s.d. b,c, Brain maps (FDR thresholded) showing Cohen’s d values for each of the 68 cortical regions (thickness) and the 14 subcortical regions and ventricles (volumes) for EO-AN versus TD (b) and ARFID versus TD (c).
Fig. 2
Fig. 2. Partition of BMI versus rEO-ED effects on brain features.
a, The effects on CT and SV of EO-acAN > TD. b, The effects on SA and SV of unARFID > TD. c, The effects of the EO-acAN > unARFID on CT, SA and SV. d, Brain maps summarizing the 35 significant correlations between BMI and CT (68 cortical regions) as well as SV (14 subcortical regions + 2 lateral ventricles) in patients with EO-AN. No correlations were significant in patients with ARFID. e, Correlations between residuals (removing the effect of age, sex and scanner) of the thickness of the right middle temporal gyrus and z-scored BMI in individuals with EO-AN (dark red dots) and ARFID (yellow dots). We selected the right middle temporal gyrus as it showed the highest correlation with BMI in patients with EO-AN. Regression lines are shown with shaded gray areas representing 95% CIs. r represents Pearson correlation coefficient.
Fig. 3
Fig. 3. Similarities of the EO-AN brain pattern with additional psychiatric conditions.
a, Distribution of effect sizes of three psychiatric conditions on regional CT (previously published by the ENIGMA consortium), as well as EO-AN (computed in this study). b, Brain maps representing patterns of abnormalities in CT reported by the ENIGMA consortium for three psychiatric conditions (Methods) and EO-AN. c, The relationship between single-nucleotide polymorphism (SNP)-based correlations (rG, provided by refs. ,) and brain-based correlations (rB, computed in this study using cortical thickness). Credit: brain and DNA icons in c, NIAID NIH BIOART.
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References

    1. Stordeur, C. et al. Early-onset restrictive food intake disorders in children: a latent class analysis. Eur. Child Adolesc. Psychiatry33, 2273–2279 (2023). - PMC - PubMed
    1. Pinhas, L. et al. Classification of childhood onset eating disorders: a latent class analysis. Int. J. Eat. Disord.50, 657–664 (2017). - PubMed
    1. Pinhas, L., Morris, A., Crosby, R. D. & Katzman, D. K. Incidence and age-specific presentation of restrictive eating disorders in children: a Canadian paediatric surveillance program study. Arch. Pediatr. Adolesc. Med.165, 895–899 (2011). - PubMed
    1. Nicholls, D. E., Lynn, R. & Viner, R. M. Childhood eating disorders: British national surveillance study. Br. J. Psychiatry198, 295–301 (2011). - PubMed
    1. Madden, S., Morris, A., Zurynski, Y. A., Kohn, M. & Elliot, E. J. Burden of eating disorders in 5–13-year-old children in Australia. Med. J. Aust.190, 410–414 (2009). - PubMed

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