Causal relationship between inflammatory proteins and attention deficit hyperactivity disorder: A
Kangning Zhou1, Qiang Zhang1, Miaomiao Liu1
1First Clinical School of Medicine, Beijing University of Chinese Medicine, Beijing, China.
Abstract:
Neuroinflammation is a potential pathogenesis of attention deficit hyperactivity disorder (ADHD). However, its consistency and specific causality remain unclear. We investigated the causal relationship between 91 inflammatory proteins and ADHD and explored the potential mediating role of 1400 serum metabolites. We obtained genome-wide association study (GWAS) data for 91 inflammatory proteins (n = 14,824), 1400 metabolites (n = 8299) and ADHD (n = 38,691) from publicly available datasets. A bidirectional 2-sample Mendelian randomization (MR) analysis was conducted to assess causal relationships between the inflammatory proteins and ADHD. Subsequently, a 2-step MR-based mediation analysis was performed to evaluate whether identified inflammatory proteins influence ADHD via specific metabolites. Sensitivity analyses verified the robustness of the results. Genetically predicted higher CD40L receptor (CD40) levels were associated with a reduced risk of ADHD (IVW odds ratio: 0.931; 95% CI, 0.894-0.970; P = .001), whereas the other 90 circulating inflammatory proteins were not significantly correlated with ADHD after false discovery rate correction. No reverse causal associations were detected for ADHD on 91 circulating inflammatory proteins. The 2-step MR analysis suggested that CD40 levels may exert an indirect effect on ADHD via N-acetylneuraminate, although the mediation effect did not reach statistical significance (mediation effect: 0.005; 95% CI, -0.000 to 0.011; mediation proportion: -7.290%; 95% CI, -15.100% to 0.506%). No significant pleiotropy, heterogeneity, or outliers were identified. This study provides genetic evidence supporting a protective role of CD40 in ADHD and highlights a putative immunometabolic pathway linking CD40 to neurodevelopmental outcomes. Our findings demonstrate the utility of integrating proteomic and metabolomic data within an MR framework to prioritize causal intermediates, informing potential directions for biomarker discovery and targeted intervention in ADHD.
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