Researchers have found evidence that children with high levels of attention-deficit/hyperactivity disorder (ADHD) symptoms show structural brain abnormalities, but treatment with stimulant medications can normalize these differences. This study, published in Neuropsychopharmacology, compared brain structures among children with varying levels of ADHD symptoms and medication use, offering insights into how these medications may help beyond symptom management.
ADHD is a prevalent neuropsychiatric disorder characterized by inattention, impulsivity, and hyperactivity, affecting about 5.3% of children worldwide. Children with ADHD often face significant challenges in social and academic settings, leading to a lower quality of life. Stimulant medications, which increase dopamine levels in the brain, are commonly prescribed to manage these symptoms.
Previous studies using structural magnetic resonance imaging (MRI) have identified brain structural abnormalities in children with ADHD, particularly in regions related to saliency detection and reward processing, such as the insula and nucleus accumbens. However, the results of these studies have been inconsistent, with some suggesting that stimulant medications can normalize these brain abnormalities, while others find no significant changes. Many of these earlier studies had small sample sizes and limited reproducibility, which made it difficult to draw definitive conclusions.
The current study aimed to overcome these limitations by utilizing a large, diverse sample from the Adolescent Brain Cognitive Development (ABCD) Study. By analyzing a more substantial and representative cohort of children, the researchers hoped to clarify whether stimulant medications can indeed normalize the brain structures associated with ADHD.
“It is a team effort for this project,” said study author Yi Zhang, a professor at Xidian University. “Our co-authors, Drs. Nora Volkow and Gene-Jack Wang, have used brain imaging methods to study the effect of psychostimulants (methylphenidate, Ritalin) on drug-naïve adult ADHD subjects since early 2000.”
“In this project, we take advantage of brain MRI data from the NIH-supported ABCD (Adolescent Brain Cognitive Development) database from 21 medical centers in the United States. The database includes brain imaging, clinical characteristics and behavioral data of children collected starting from about 9 years old. The ABCD project will follow up these children for 10 years. Our project used data from the early year (9-10 years old) of these children.”
The sample consisted of 7,126 children aged 9-10 years, who were divided into three groups based on their ADHD symptoms and medication status:
- Stim Low-ADHD: This group included 273 children with low ADHD symptoms who were receiving stimulant medication.
- No-Med ADHD: This group comprised 1,002 children with high ADHD symptoms who were not receiving any medication.
- Typically Developing Controls (TDC): This group consisted of 5,378 children with low ADHD symptoms who were not receiving any medication.
The researchers employed latent class analysis (LCA) to categorize the children based on their ADHD symptoms, using the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS) criteria. This method allowed the researchers to identify distinct subgroups of children with similar symptom patterns.
They also used linear mixed-effects models to analyze differences in brain structure among the three groups, while controlling for variables such as age, sex, race, socioeconomic status, body mass index, and family background. High-resolution structural magnetic resonance imaging (MRI) was used to assess brain structures.
The study found significant differences in brain structures between the No-Med ADHD group and the other two groups. Specifically, children with high ADHD symptoms who were not on medication (No-Med ADHD) exhibited lower cortical thickness in the right insula and smaller subcortical volume in the left nucleus accumbens compared to both the stimulant-treated children (Stim Low-ADHD) and typically developing controls (TDC). These findings suggest that children with untreated ADHD have structural abnormalities in brain regions associated with saliency and reward processing.
In contrast, there were no significant differences in brain structures between the Stim Low-ADHD group and the TDC group. This indicates that stimulant medications may normalize the brain structural abnormalities associated with ADHD. The stimulant-treated children showed brain structures that were similar to those of typically developing children, suggesting that the medications not only alleviate ADHD symptoms but also potentially address underlying neurobiological deficits.
“We found children with ADHD appeared to have structural abnormalities in brain regions associated with saliency and reward processing,” Zhang told PsyPost. “Treatment with stimulant medications not only improved the ADHD symptoms but also normalized these brain structural abnormalities.”
While these findings are promising, the study has some limitations. Firstly, it is cross-sectional, meaning it captures a snapshot in time and cannot definitively establish causation. Longitudinal studies following children over time are needed to confirm the long-term effects of stimulant medications on brain development.
Secondly, the study did not account for the dosage and duration of stimulant medication use, which could influence the extent of brain changes. Future research should consider these factors to better understand how different treatment regimens impact brain structure.
Additionally, the study only included children aged 9-10 years, so the findings may not apply to older children or adults with ADHD. Further research is needed to explore how these brain changes evolve with age and continued medication use.
“We shall follow up these children in next few years to understand their brain development,” Zhang said.
The study, “Stimulant medications in children with ADHD normalize the structure of brain regions associated with attention and reward,” was authored by Feifei Wu, Wenchao Zhang, Weibin Ji, Yaqi Zhang, Fukun Jiang, Guanya Li, Yang Hu, Xiaorong Wei, Haoyi Wang, Szu-Yung (Ariel) Wang, Peter Manza, Dardo Tomasi, Nora D. Volkow, Xinbo Gao, Gene-Jack Wang, and Yi Zhang.
