ArticleFrontiers in psychiatry2025
Integrated transcriptomic and network analysis reveals candidate immune-metabolic biomarkers in children with the inattentive type of ADHD.
Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is a clinically heterogeneous neurodevelopmental disorder. Its inattentive presentation (ADHD-I) is a common subtype characterized predominantly by difficulties in sustaining attention, organization skills, and task completion. The biological foundations of ADHD-I remain unclear, hampering the development of effective treatments. This study aimed to identify potential ADHD-I biomarker candidates to guide the therapeutic strategies. Methods: We analyzed transcriptome sequencing data from a cohort of 32 children (15 control, 17 ADHD-I; aged 6-12 years;81.2% male). All ADHD-I participants were medication-naïve and without comorbid neurodevelopmental or major psychiatric conditions) to systematically identify potential biomarkers for ADHD-I. Candidate genes were identified by integrating differential expression analysis with weighted gene co-expression network analysis (WGCNA) modules. High-confidence biomarkers were selected via a multi-step pipeline combining protein-protein interaction (PPI) network analysis and machine learning feature selection (LASSO regression, Boruta algorithm). Biomarker performance was evaluated using ROC and gene expression analyses, and a predictive nomogram was developed. The ADHD-I molecular landscape was explored through functional enrichment, immune cell profiling, pharmacological screening, and ligand-receptor interaction modeling. Results: Cluster of Differentiation 180(CD180) and Cytochrome c Oxidase Assembly Factor 3(COA3) were identified as potential ADHD-I biomarker candidates. Both showed high preliminary diagnostic accuracy (AUC > 0.8) and significantly elevated expression in ADHD - I cohorts. The nomogram incorporating these biomarkers showed preliminary predictive accuracy for ADHD-I risk stratification (AUC = 0.878) in this cohort. Pathway enrichment analysis further localized CD180 and COA3 to the dorsoventral axis formation pathway, suggesting their role in developmental patterning. Five significant differential immune cell types were identified between ADHD-I and control samples. Both biomarkers demonstrated the significant positive correlation with gamma delta T cells and the strongest negative correlation with eosinophils. Compound prediction showed that 20 compounds such as benzo(a)pyrene targeted CD180, and benzo(a)pyrene had a strong binding ability to CD18 (ΔG = -8.1 kcal/mol). Conclusion: The study identified CD180 and COA3 as candidate biomarkers for ADHD-I, which may provide new clues into the mechanism of ADHD-I and potential therapeutic targets.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.