The Metabolome Profiling and Pathway Analysis of ADHD

Overview

The purpose of this study is to understand the pathophysiological mechanisms of ADHD, especially the metabolomic pathway related to the behavioral/neuropsychological deficits of ADHD. To identify specific metabolites that show significant differences between ADHD and control groups, both liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry will be performed. In addition, the behavioral measures include ADHDRS-IV, SNAP-IV, CBCL, CGI-ADHD-S, SAICA, and Family APGAR-C. Neuropsychological testing, including CPT and CANTAB, will be performed. Conditional logistic regression and partial least squares discriminant analysis will be applied to identify significant metabolites for ADHD. Pathway enrichment and topology analyses will be conducted to evaluate the regulated pathways.

Because attention deficit hyperactivity disorder (ADHD) is an early onset and long-term impairing disorder with tremendous impact on individuals, families, and societies, detection and diagnosis are very important for ADHD. Current diagnosis of ADHD relies mainly on clinical observation and interview tools that may involve a great subjective variability, and thus the investigation of objective biomarkers for ADHD is warranted. Metabolomics is the study of a biologic process involving all metabolites that are end products of the cellular process in a whole organism. Because metabolites represent the downstream expression of genome, transcriptome, and proteome, metabolomic profiles are more proximal to the behavioral phenotypes of ADHD. Analyzing metabolic differences between children with ADHD and healthy controls will provide insight into underlying disease pathology. To date, there has been no metabolomics study on ADHD. In this 3-year project, the investigators will perform a metabolomics analysis of serum to identify potential biomarkers for the behavioral and neuropsychological deficits of ADHD. This is a 3-year project. After careful calculation of sample size, the investigators will recruit 120 drug-naïve children with ADHD, aged 7-18, and 120 healthy controls with matched age, sex and BMI. Using both liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry, serum-based metabolomic profiling will be performed. The behavioral measures include ADHDRS-IV, SNAP-IV, CBCL, CGI-ADHD-S, SAICA, and Family APGAR-C. Neuropsychological testing, including CPT and CANTAB, will be performed. Conditional logistic regression and partial least squares discriminant analysis will be applied to identify significant metabolites for ADHD. Pathway enrichment and topology analyses will be conducted to evaluate the regulated pathways. Using a matched study design, the investigators anticipate to identify specific metabolites that show significant differences between ADHD and control groups. In addition, results of pathway analysis may offer more biological understanding in explaining the underlying metabolic regulation among children with ADHD. This findings will significantly contribute to the knowledge of the pathophysiological mechanisms of ADHD, especially the metabolomic pathway related to the behavioral/neuropsychological deficits of ADHD.