Magnetic resonance imaging (MRI) scans of children showing symptoms of avoidant/restrictive food intake disorder (ARFID) show differences in certain brain regions relative to children without ARFID symptoms. Findings from this work serve to improve our general understanding of ARFID and may help inform on ARFID-related services or our understanding of ARFID.
Background
Avoidant/restrictive food intake disorder (ARFID) is a feeding and eating disorder that was introduced in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), published in 2013 (American Psychiatric Association, 2013). ARFID is characterised by a restriction or avoidance of food intake for a variety of reasons and three underpinning drivers of ARFID consist of lack of interest in food, sensory sensitivity associated with food and fear of aversive consequences, such as choking or vomiting (DSM-5-TR). Despite the preconception that those with ARFID are simply ‘fussy eaters’, ARFID can pose significant adverse effects on mental and physical health. ARFID can impact one’s weight and body similar to those with anorexia nervosa (Lange et al., 2019; Alberts et al. 2020) and yet, is regarded as significantly less harmful (Ellis et al., 2020).
A decade on from the inclusion of ARFID as a diagnostic criteria, literature on the disorder is limited and extensively varied. For instance, referrals for ARFID are increasing, but neither the National Institute of Health and Care Excellence (NICE) nor the Scottish Collegiate Guidelines Network (SIGN) are able to provide guidelines on interventions or treatment for ARFID (Sader et al., 2024). Prevalence rates for ARFID are highly varied across global and clinical populations, ranging between 0.3%-17.9% and 0.9-32% respectively (Sanchez-Cerezo et al., 2023). Importantly, there are no current studies evaluating the brain structure of those with ARFID or ARFID-like states that may help with understanding biological drivers associated with the feeding and eating disorder.
The current literature on ARFID begs the following question: are there structural differences in the brains of children with ARFID symptoms?
Main Content and Going Forward
To understand whether children with ARFID symptoms indeed exhibit differences in brain structure relative to children not presenting with ARFID symptoms, an international group of researchers led by Dr Michelle Sader analysed brain scans from 1,977 10-year-old participants from the Generation R Study, a population-based Dutch cohort from Rotterdam. Children were classified with ARFID using the ARFID Index (Sader et al., 2023), a validated evaluative tool meant to reflect DSM-5 diagnostic criteria that use parent- and child-reported measures to characterise symptoms in research settings. Once children from the Generation R study were characterised as expressing or not expressing ARFID symptomatology, T1-weighted MRI scans were used to compare brain volume, surface area, and cortical thickness between groups.
From 1,977 children, 121, or 6.1% presented with ARFID symptoms. Analysis of MRI scans between those with versus those without ARFID symptoms identified differences in cortical thickness, which is a measurement of the depth of the outer layer of the brain. Significantly greater cortical thickness was seen in the frontal (p=0.00743; d=0.21) and superior frontal cortex (p=6.56E-04; d=0.28) in children with ARFID symptoms. These regions are associated with conflict anticipation, attentional processing and inhibition control. Interestingly, previous work with this cohort identified that children with ARFID symptoms exhibited increased levels of anxiety, depression, and obsessive-compulsive disorder, as well as increased levels of attention deficit hyperactivity disorder and increased Autistic characteristics (Sader et al., 2023). Future imaging-based research on ARFID would benefit from examining whether structural differences in the brain are associated with comorbidity or co-occurrence of other psychiatric or neurodevelopmental conditions.
Findings from this research suggest the frontal and superior frontal cortex may serve as neural correlates specific to ARFID symptomatology, and potentially point towards altered executive function.
![Increased thickness of the frontal and superior frontal cortex seen in children with ARFID symptoms relative to children not presenting with ARFID symptomatology]](https://www.acamh.org/app/uploads/2024/11/figure1.png)
Conclusions
To our knowledge, this is the first structural MRI study associated with ARFID. However, there are important considerations that put findings from this research into perspective. For instance, no self-report or semi-structured interviews to classify ARFID are currently available within the Generation R dataset, meaning the research team constructed the ARFID Index to evaluate children exhibiting disorder symptomatology, rather than a formal diagnosis of ARFID. Additionally, the data used for this research focused on 10-year-old children, and as such neuroanatomical findings cannot be generalised to adult populations. Despite these limitations, findings from this work further our physiological understanding of ARFID, and may assist with clinician understanding of ARFID as well as inform on ways with which professionals can treat and support those with this feeding and eating disorder.
This work investigating neural correlates associated with ARFID symptoms serve as a foundation for future neuroimaging research into this feeding and eating disorder.
NB this blog has been peer-reviewed
References
- Primary paper: Sader, M., Harris, H., Waiter, G., Jansen, P., Williams, J.H.G., White, T. (2024) Neural Correlates of Children with Avoidant Restrictive Food Intake Disorder (ARFID) Symptoms: Large-Scale Neuroanatomical Analysis of a Paediatric Population. Journal of Child Psychology and Psychiatry. https://doi.org/10.1111/jcpp.14086
- American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed.). American Psychiatric Association.
- American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders, text revision DSM-5-TR. (5th ed.). American Psychiatric Association.
- Alberts, Z., Fewtrell, M., Nicholls, D. E., Biassoni, L., Easty, M., & Hudson, L. D. (2020). Bone mineral density in anorexia nervosa versus avoidant restrictive food intake disorder. Bone, 134, 115307.
- Lange, C. A., Ekedahl Fjertorp, H., Holmer, R., Wijk, E., & Wallin, U. (2019). Long‐term follow‐up study of low‐weight avoidant restrictive food intake disorder compared with childhood‐onset anorexia nervosa: Psychiatric and occupational outcome in 56 patients. International Journal of Eating Disorders, 52(4), 435-438.
- Ellis, J. M., Essayli, J. H., Zickgraf, H. F., Rossi, J., Hlavka, R., Carels, R. A., & Whited, M. C. (2020). Comparing stigmatizing attitudes toward anorexia nervosa, binge-eating disorder, avoidant-restrictive food intake disorder, and subthreshold eating behaviors in college students. Eating behaviors, 39, 101443.
- Sader, M., Chawner, S., Nimbley, E., Gillespie-Smith, K., & Duffy, F. (2024). ARFID: A BRIEF EVIDENCE REVIEW FOR EATING DISORDERS AWARENESS WEEK 2024. Eating Disorder Awareness Week 2024.
- Sanchez‐Cerezo, J., Nagularaj, L., Gledhill, J., & Nicholls, D. (2023). What do we know about the epidemiology of avoidant/restrictive food intake disorder in children and adolescents? A systematic review of the literature. European Eating Disorders Review, 31(2), 226-246.
- Sader, M., Harris, H. A., Waiter, G. D., Jackson, M. C., Voortman, T., Jansen, P. W., & Williams, J. H. (2023). Prevalence and characterization of avoidant restrictive food intake disorder in a pediatric population. JAACAP Open, 1(2), 116-127.
About the author
Dr. Michelle Sader is a neuroscientist and postdoctoral research fellow at the University of Aberdeen, currently working on the Eating Disorders and Autism Collaborative (EDAC) research network (EDACResearch.co.uk). Her PhD focused on brain structure associated with emotional regulation and appetite. Currently, her work focuses on using brain imaging techniques to understand brain differences associated with eating disorders such as anorexia nervosa, feeding and eating disorders such as avoidant/restrictive food intake disorder (ARFID), and across neurotypes such as autism.
