ADHD Biotypes Identified for Treatment
JAMA Psychiatry published research identifying three distinct ADHD biotypes using morphometric similarity networks for better patient stratification. Separately, researchers found that resting-state brain dynamics can predict how patients respond to drug-modulated cognitive control treatments. These advances could enable more personalized ADHD treatment approaches.
The current method for diagnosing Attention-Deficit/Hyperactivity Disorder (ADHD) relies on the DSM-5, which outlines criteria for inattentive, hyperactive-impulsive, or combined presentations. This diagnostic process is based on observed behaviors and reported symptoms rather than biological markers. Treatment typically involves a combination of medication, such as stimulants or non-stimulants, and behavioral therapies. The research published in *JAMA Psychiatry* introduces a new approach by identifying three distinct ADHD "biotypes" based on brain imaging. A combined effort from Australian and Chinese researchers utilized morphometric similarity networks, a method of analyzing brain structure, to categorize individuals into groups defined by severe-combined symptoms with emotional dysregulation, predominantly hyperactive/impulsive traits, or predominantly inattentive characteristics. Each of these biotypes was linked to specific alterations in different brain regions. This move toward biologically defined subtypes is not entirely new; the classification of ADHD has evolved over time. The DSM-IV, for instance, previously used the term "subtypes" before the DSM-5 shifted to "presentations" to better capture how symptoms can change over a person's lifetime. However, this new research provides a potential neurobiological basis for these different presentations. The second study highlighted, which investigated resting-state brain dynamics, adds another layer to personalizing treatment. Research in this area has shown that brain activity patterns, even when a person is not focused on a specific task, may predict how they will respond to different medications. For example, connectivity within certain brain networks, like the cingulo-opercular network, has been associated with the effectiveness of psychostimulant treatment. The ultimate goal of this type of research is to move beyond the current trial-and-error approach to prescribing ADHD medication. While stimulants are effective for many, they don't work for everyone, and some individuals experience significant side effects. By identifying biological markers that can predict treatment response, clinicians could one day select the most effective medication and dosage for an individual from the outset. These advancements could lead to a more precise and personalized approach to ADHD care. Instead of a one-size-fits-all diagnosis and treatment plan, physicians might use brain imaging to identify a patient's specific biotype and predict their response to various therapies, leading to more effective and targeted interventions.
