Abstract
BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children, increasingly associated with immune system dysregulation. Emerging evidence suggests that alterations in circulating immune cells, particularly lymphocyte subsets, may reflect neuroinflammatory processes involved in ADHD pathophysiology. However, the precise immunophenotypic characteristics of peripheral lymphocytes in children with ADHD remain poorly defined. While immune biomarkers such as cytokines have been studied, their clinical utility is limited. In contrast, flow cytometric profiling of lymphocyte subpopulations offers a practical tool for immune monitoring. Here, we investigated the distribution of peripheral lymphocyte subsets in drug-naïve children with ADHD and evaluated their potential diagnostic value. METHODS: Forty-two drug-naïve ADHD children and 45 healthy controls provided a fasting blood sample for complete blood count (CBC) and multi-parameter flow cytometry. T cells (CD3(+)), CD4(+)/CD8(+) subsets, B cells (CD19(+)), NK cells (CD16(+)/CD56(+)), regulatory T cells (CD4(+)CD25(+)CD127(-)), and naïve (CD45RA(+))/memory (CD45RO(+)) T cells were quantified. Receiver operating characteristic (ROC) curves with logistic regression assessed each marker's ability to predict ADHD. RESULTS: Groups were matched for age, sex, and body mass index (BMI). ADHD children had slightly higher neutrophils but lower monocytes and neutrophil-to-lymphocyte ratio (NLR); total leukocytes, lymphocytes, hemoglobin, and platelets were similar. Monocyte count and NLR each yielded area under ROC curve (AUC) >0.60, and a combined model (neutrophils, monocytes and NLR) achieved an AUC of 0.8487 (P<0.0001). Immunophenotyping showed no differences in total T, CD4(+), B, or NK cells, but ADHD subjects had higher CD8(+) percentages/counts, elevated Treg frequencies, and a lower CD4/CD8 ratio; each parameter alone had an AUC >0.60, and a combined model reached an AUC of 0.8095. Further, ADHD children exhibited expansion of naïve-like T cells and reduction of memory-associated T cells; several of these subsets had AUCs >0.70, and a five-marker phenotype model achieved an AUC of 0.9910. CONCLUSIONS: ADHD is characterized by altered innate cell ratios, increased CD8(+) and regulatory T cells, and a skewed naïve/memory T-cell balance. Combined hematological and immunophenotypic models demonstrated excellent diagnostic accuracy, supporting lymphocyte as a source of novel ADHD biomarkers and underscoring systemic immune dysregulation.