Objective
Genetic studies of attention-deficit/hyperactivity disorder (ADHD) generally use discrete DSM-IV subtypes to define diagnostic status. To improve correspondence between phenotypic variance and putative susceptibility genes, multivariate classification methods such as latent class analysis (LCA) have been proposed. The aim of this study was to perform LCA in a sample of 1,010 individuals from a nationwide recruitment of unilineal nuclear families with at least one child with ADHD and another child either affected or clearly unaffected.
Method
LCA models containing one through 10 classes were fitted to data derived from all DSM-IV symptoms for ADHD, oppositional defiant disorder, and conduct disorder (CD), as well as seven items that screen for anxiety and depression from the National Initiative for Children's Healthcare Quality Vanderbilt Assessment Scale for Parents.
Results
We replicated six to eight statistically significantly distinct clusters, similar to those described in other cross-cultural studies, mostly stable when comorbidities are included. For all age groups, anxiety and depression are strongly related to Inattentive and Combined types. Externalizing symptoms, especially CD, are strongly associated with the Combined type of ADHD. Oppositional defiant disorder symptoms in young children are associated with either conduct disorder or anxiety-related symptoms.
Conclusions
Methods such as LCA allow inclusion of information about comorbidities to be quantitatively incorporated into genetic studies. LCA also permits incorporation of milder but still impairing phenotypes than are allowed using the DSM-IV. Such methods may be essential for analyses of large multicenter datasets and relevant for future clinical classifications. This population-based ADHD classification may help resolve the contradictory results presented in molecular genetic studies.
Ideally, one day specific genes with major effects and specific risk factors with which they interact will be identified and we will be able to implement personalized medicine. Knowledge of such genes will allow us to identify specific diagnostic biological markers. In addition, defining the target genes is the first step in developing novel drug therapies to treat the ADHD symptoms that lead to impairment. Furthermore, such markers could also identify at risk individuals at a younger age in order to implement treatments sooner to decrease the severity of ADHD symptoms or even to prevent future ADHD symptomatology.
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