Can biomarkers be used to diagnose attention deficit hyperactivity disorder?

Virtual reality-assisted prediction of adult ADHD based on eye tracking, EEG, actigraphy and behavioral indices: a machine learning analysis of independent training and test samples

Given the heterogeneous nature of attention-deficit/hyperactivity disorder (ADHD) and the absence of established biomarkers, accurate diagnosis and effective treatment remain a challenge in clinical practice. This study investigates the predictive utility of multimodal data, including eye tracking, EEG, actigraphy, and behavioral indices, in differentiating adults with ADHD from healthy individuals. Using a support vector machine model, we analyzed independent training (n = 50) and test (n = 36) samples from two clinically controlled studies. In both studies, participants performed an attention task (continuous performance task) in a virtual reality seminar room while encountering virtual distractions. Task performance, head movements, gaze behavior, EEG, and current self-reported inattention, hyperactivity, and impulsivity were simultaneously recorded and used for model training. Our final model based on the optimal number of features (maximal relevance minimal redundancy criterion) achieved a promising classification accuracy of 81% in the independent test set. Notably, the extracted EEG-based features had no significant contribution to this prediction and therefore were not included in the final model. Our results suggest the potential of applying ecologically valid virtual reality environments and integrating different data modalities for enhancing robustness of ADHD diagnosis.

Quantum dots-based multiplexed immunosensors for accurate diagnosis of attention deficit hyperactivity disorder in childhood

Attention-deficit/hyperactivity disorder (ADHD) lacks objective diagnostic markers. In clinical settings, reliance on subjective judgments can often lead to missed or misdiagnoses. Some biomarkers have been reported to be associated with ADHD, but using one biomarker alone is not enough. To address this, we developed a fluorescent immunoassay platform based on quantum dots (QDs) to detect assay capable of detecting and quantifying multiple biomarkers simultaneously. Specifically, we were able to the simultaneously detect brain-derived neurotrophic factor, tumor necrosis factor-alpha, interleukin-6 and ferritin using different emission spectra QDs. The QD-based multiplexed immunoassay displayed a low detection of limit in the range of 0.021-0.068 pg/mL, and the assay showed satisfactory reproducibility and precision. We then quantified all four targets from ADHD patient's plasma samples, where it showed remarkable consistency with clinical test for ADHD diagnosis. This methodological comparison supports the diagnosis of ADHD using our assay.

Expression Patterns of miRNAs in Egyptian Children with ADHD: Clinical Study with Correlation Analysis

ADHD has huge knowledge gaps concerning its etiology. MicroRNAs (miRNAs) provide promising diagnostic biomarkers of human pathophysiology and may be a novel therapeutic option. The aim was to investigate the levels of miR-34c-3p, miR-155, miR-138-1, miR-296-5p, and plasma brain-derived neurotrophic factor (BDNF) in a group of children with ADHD compared to neurotypicals and to explore correlations between these measures and some clinical data. The participants were children with ADHD in Group I (N = 41; age: 8.2 ± 2) and neurotypical ones in Group II (N = 40; age: 8.6 ± 2.5). Group I was subjected to clinical examination, the Stanford Binet intelligence scale-5, the preschool language scale, and Conner's parent rating scale-R. Measuring the expression levels of the miRNAs was performed by qRT-PCR for all participants. The BDNF level was measured by ELISA. The lowest scores on the IQ subtest were knowledge and working memory. No discrepancies were noticed between the receptive and expressive language ages. The highest scores on the Conner's scale were those for cognitive problems. Participants with ADHD exhibited higher plasma BDNF levels compared to controls (p = 0.0003). Expression patterns of only miR-34c-3p and miR-138-1 were downregulated with significant statistical differences (p˂0.01). However, expression levels of miR-296-5p showed negative correlation with the total scores of IQ (p = 0.03). MiR-34c-3p, miR-138-1, while BDNF showed good diagnostic potential. The downregulated levels of miR-34c-3p and miR-138-1, together with high BDNF levels, are suggested to be involved in the etiology of ADHD in Egyptian children. Gender differences influenced the expression patterns of miRNAs only in children with ADHD.

Metabolomic Markers in Attention-Deficit/Hyperactivity Disorder (ADHD) among Children and Adolescents-A Systematic Review

Attention-Deficit/Hyperactivity Disorder (ADHD), characterized by clinical diversity, poses diagnostic challenges often reliant on subjective assessments. Metabolomics presents an objective approach, seeking biomarkers for precise diagnosis and targeted interventions. This review synthesizes existing metabolomic insights into ADHD, aiming to reveal biological mechanisms and diagnostic potentials. A thorough PubMed and Web of Knowledge search identified studies exploring blood/urine metabolites in ADHD-diagnosed or psychometrically assessed children and adolescents. Synthesis revealed intricate links between ADHD and altered amino acid metabolism, neurotransmitter dysregulation (especially dopamine and serotonin), oxidative stress, and the kynurenine pathway impacting neurotransmitter homeostasis. Sleep disturbance markers, notably in melatonin metabolism, and stress-induced kynurenine pathway activation emerged. Distinct metabolic signatures, notably in the kynurenine pathway, show promise as potential diagnostic markers. Despite limitations like participant heterogeneity, this review underscores the significance of integrated therapeutic approaches targeting amino acid metabolism, neurotransmitters, and stress pathways. While guiding future research, this overview of the metabolomic findings in ADHD suggests directions for precision diagnostics and personalized ADHD interventions.

The Kynurenine Pathway in Attention-Deficit/Hyperactivity Disorder: A Systematic Review and Meta-Analysis of Blood Concentrations of Tryptophan and Its Catabolites

Preliminary evidence shows that the kynurenine pathway (KP) may be altered in attention-deficit/hyperactivity disorder (ADHD). We thus conducted a systematic review and meta-analysis exploring the peripheral blood concentrations of tryptophan catabolites (TRYCATs) in people with ADHD. We searched the main electronic databases up to 7th December 2023. Standardised mean differences (SMDs) with 95% confidence intervals (95%CIs) were used to compare TRYCAT concentrations between participants with ADHD and healthy controls (HCs). We included eight studies. Random-effects meta-analyses found higher kynurenine (SMD = 0.56; 95%CI: 0.04 to 1.08; p = 0.033; I2 = 90.3%) and lower kynurenic acid (SMD = -0.33; 95%CI: -0.49 to -0.17; p < 0.001; I2 = 0%) concentrations in people with ADHD compared to HCs. Additional analyses on drug-free children with ADHD showed higher tryptophan (SMD = 0.31; 95%CI: 0.11 to 0.50; p = 0.002; I2 = 0%) and kynurenine (SMD = 0.74; 95%CI: 0.30 to 1.17; p < 0.001; I2 = 76.5%), as well as lower kynurenic acid (SMD = -0.37; 95%CI: -0.59 to -0.15; p < 0.001; I2 = 0%) blood levels, as compared to HCs. Despite some limitations, our work provides preliminary evidence on KP alterations in ADHD that may suggest decreased neuroprotection. Further research is needed to clarify the role of the KP in ADHD.

Molecular Mechanisms Underlying NMDARs Dysfunction and Their Role in ADHD Pathogenesis

Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, although the aetiology of ADHD is not yet understood. One proposed theory for developing ADHD is N-methyl-D-aspartate receptors (NMDARs) dysfunction. NMDARs are involved in regulating synaptic plasticity and memory function in the brain. Abnormal expression or polymorphism of some genes associated with ADHD results in NMDAR dysfunction. Correspondingly, NMDAR malfunction in animal models results in ADHD-like symptoms, such as impulsivity and hyperactivity. Currently, there are no drugs for ADHD that specifically target NMDARs. However, NMDAR-stabilizing drugs have shown promise in improving ADHD symptoms with fewer side effects than the currently most widely used psychostimulant in ADHD treatment, methylphenidate. In this review, we outline the molecular and genetic basis of NMDAR malfunction and how it affects the course of ADHD. We also present new therapeutic options related to treating ADHD by targeting NMDAR.

Altered Urine Microbiome in Male Children and Adolescents with Attention-Deficit Hyperactivity Disorder

While interest in developing the human microbiome as a biomarker for attention-deficit hyperactivity disorder (ADHD) is increasing, there has been limited exploration in utilizing urine samples. In this study, we analysed urine microbiome profiles by extracting 16S ribosomal DNA from purified bacteria-derived extracellular membrane vesicles obtained from urine samples. Sequencing libraries were constructed by amplifying V3-V4 hypervariable regions sequenced using Illumina MiSeq. Profiles of male Korean children and adolescents with ADHD (n = 33) were compared with healthy sex-matched controls (n = 39). Statistically controlling for age, we found decreased alpha diversity in the urine bacteria of the ADHD group, as evidenced by reduced Shannon and Simpson indices (p < 0.05), and significant differences in beta diversity between the two groups (p < 0.001). The phyla Firmicutes and Actinobacteriota, as well as the genera Ralstonia and Afipia, were relatively more abundant in the ADHD group. The phylum Proteobacteria and the genera Corynebacterium and Peptoniphilus were more abundant in the control group. Notably, the genus Afipia exhibited significant correlations with the Child Behavior Checklist Attention Problems score and DSM-oriented ADHD subscale. This study is the first to propose the urine microbiome as a potential biomarker for pediatric ADHD.