Examining Differences in the Genetic and Functional Architecture of Attention-Deficit/Hyperactivity Disorder Diagnosed in Childhood and Adulthood
Sophie Breunig1,2, Jeremy M Lawrence1,2, Isabelle F Foote1,2
1Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado.
Background:
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with diagnostic criteria requiring symptoms to begin in childhood. We investigated whether individuals diagnosed as children differ from those diagnosed in adulthood with respect to shared and unique architecture at the genome-wide and gene expression level of analysis.
Methods:
We used genomic structural equation modeling (SEM) to investigate differences in genetic correlations (r) of childhood-diagnosed (n = 14,878) and adulthood-diagnosed (n = 6961) ADHD with 98 behavioral, psychiatric, cognitive, and health outcomes. We went on to apply transcriptome-wide SEM to identify functional annotations and patterns of gene expression associated with genetic risk sharing or divergence across the ADHD subgroups.
Results:
Compared with the childhood subgroup, adulthood-diagnosed ADHD exhibited a significantly larger negative r with educational attainment, the noncognitive skills of educational attainment, and age at first sexual intercourse. We observed a larger positive r for adulthood-diagnosed ADHD with major depression, suicidal ideation, and a latent internalizing factor. At the gene expression level, transcriptome-wide SEM analyses revealed 22 genes that were significantly associated with shared genetic risk across the subtypes that reflected a mixture of coding and noncoding genes and included 15 novel genes relative to the ADHD subgroups.
Conclusions:
This study demonstrated that ADHD diagnosed later in life shows much stronger genetic overlap with internalizing disorders and related traits. This may indicate the potential clinical relevance of distinguishing these subgroups or increased misdiagnosis for those diagnosed later in life. Top transcriptome-wide SEM results implicated genes related to neuronal function and clinical characteristics (e.g., sleep).
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