TMS-biomarkers discovery in children and adolescents with neurological disorders: A systematic review and meta-analysis.

This systematic review and meta-analysis examined the application of transcranial magnetic stimulation (TMS) electrophysiological biomarkers in children and adolescents, focusing on their role in assessing neurological disorders. We synthesized data from 26 studies to compare TMS measures between healthy children/adolescents and adults, and evaluated their diagnostic discriminability in attention-deficit/hyperactivity disorder (ADHD), Tourette syndrome (TS), major depressive disorder (MDD), autism spectrum disorder (ASD), and cerebral palsy (CP). Key findings revealed that, ADHD was associated with increased SICI ratios and shortened cortical silent period (CSP); TS showed reduced CSP; MDD exhibited decreased CSP, enhanced intracortical facilitation (ICF), and weakened long-interval intracortical inhibition (LICI). Additionally, atypical interhemispheric asymmetry in TMS measures was observed in ASD and CP. These results provide preliminary evidence that TMS-derived electrophysiological biomarkers may reflect critical developmental and pathological variations in cortical excitability and inhibition. While these findings represent preliminary evidence, they highlight the potential of TMS as a supportive tool for early clinical screening and offer valuable mechanistic insights that could eventually inform more personalized intervention strategies for pediatric neurological disorders. IMPLICATIONS: This meta-analysis provides preliminary evidence for the potential for the potential diagnostic utility of TMS-derived neurophysiological biomarkers in children and adolescents with neurological disorders. The diversity of TMS biomarkers and their observed relevance to disease-specific neuropathology suggest that TMS may offer a non-invasive, multidimensional approach to characterizing brain state in pediatric populations. While further large-scale studies are needed to confirm these trends, our findings offer insights that could eventually inform more precise clinical evaluation and early intervention strategies.