The main goal of the proposed program of research is to use specific gene variants and environmental measures to clarify the nature of gene-environment interactions in Attention Deficit Hyperactivity Disorder (ADHD) and to improve our ability to predict which children require preventive interventions for ADHD and its associated adverse outcomes. We will accomplish this goal by collecting DNA samples from subjects who have already participated in two ongoing longitudinal family studies of ADHD. Our basic strategy is to use the ecogenetic approach described by Khoury et al. This method improves risk prediction by examining genetically mediated differences in susceptibility to environmental agents. In the proposed work, we will collect DNA samples from the ADHD proband and their family members who have participated in our two longitudinal family studies comprising 1,040 subjects in families ascertained through ADHD children. The proposal has three main aims: 1) to predict adverse outcomes among ADHD children and their siblings; 2) to assess the accuracy of risk prediction and 3) to create a genetics resource for ecogenetic studies. There can be little doubt that ADHD is caused by the confluence of genes and environment. Because some susceptibility genes have been found and some environmental causes identified, ADHD is an ideal disorder for the application of ecogenetic models. Moreover, because ADHD children are at high risk for multiple adverse outcomes, they are a clinically meaningful target group for prevention studies seeking to prevent these outcomes. Predicting adverse outcomes among ADHD children has clinical, scientific and public health implications. Such efforts can help identify etiologic risk factors associated with more impaired outcome in ADHD and can characterize early predictors of persistence and morbidity of this disorder. Moreover, predicting the course of ADHD could help design improved secondary prevention programs aimed at reducing the morbidity of ADHD throughout childhood and adolescence. From a public health perspective, the ability to predict course and clinical complications could help focus societal resources on those at higher risk for persistent illness with complicated outcomes. One strength of the proposed study is that we have also collected data on the siblings of ADHD probands. Using ecogenetic methods, we will be able to predict which siblings are at highest risk for ADHD. Such data would be useful for clinicians faced with parents of ADHD children who are concerned with the future of their non-ADHD children. Ecogenetic prediction models could one day provide a rational method for clinicians to recommend preventive interventions for siblings of ADHD children. Although longitudinal studies of ADHD have provided some evidence that outcome can be predicted from clinical assessments, the accuracy of prediction is low, suggesting that variables from other domains should be entered into the prediction equation. Our plan is to use genes as new predictors of outcome is innovative because no prior studies have used specific gene variants to predict course and outcome among ADHD children. Furthermore, no studies have used an ecogenetic approach to sharpen the accuracy of risk prediction.
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