Format

Send to

Choose Destination
Am J Med Genet B Neuropsychiatr Genet. 2016 Sep;171(6):815-26. doi: 10.1002/ajmg.b.32446. Epub 2016 Mar 22.

Pathway analysis in attention deficit hyperactivity disorder: An ensemble approach.

Author information

1
Division of Bioinformatics & Computational Biology, Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon.
2
OHSU Knight Cancer Institute, Portland, Oregon.
3
Oregon Clinical and Translational Research Institute, Portland, Oregon.
4
Departments of Psychiatry and Neuroscience & Physiology, State University of New York, Syracuse, New York.
5
K.G. Jebsen Centre for Neuropsychiatric Disorders, Department of Biomedicine, University of Bergen, Bergen, Norway.
6
Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
7
Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon.
8
Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon.

Abstract

Despite a wealth of evidence for the role of genetics in attention deficit hyperactivity disorder (ADHD), specific and definitive genetic mechanisms have not been identified. Pathway analyses, a subset of gene-set analyses, extend the knowledge gained from genome-wide association studies (GWAS) by providing functional context for genetic associations. However, there are numerous methods for association testing of gene sets and no real consensus regarding the best approach. The present study applied six pathway analysis methods to identify pathways associated with ADHD in two GWAS datasets from the Psychiatric Genomics Consortium. Methods that utilize genotypes to model pathway-level effects identified more replicable pathway associations than methods using summary statistics. In addition, pathways implicated by more than one method were significantly more likely to replicate. A number of brain-relevant pathways, such as RhoA signaling, glycosaminoglycan biosynthesis, fibroblast growth factor receptor activity, and pathways containing potassium channel genes, were nominally significant by multiple methods in both datasets. These results support previous hypotheses about the role of regulation of neurotransmitter release, neurite outgrowth and axon guidance in contributing to the ADHD phenotype and suggest the value of cross-method convergence in evaluating pathway analysis results.

KEYWORDS:

ADHD; GWAS; pathway analyses

PMID:
27004716
PMCID:
PMC4983253
[Available on 2017-03-01]
DOI:
10.1002/ajmg.b.32446
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Wiley Icon for PubMed Central
Loading ...
Support Center