Can Genetics Predict Response to Complex Behavioral Interventions? Evidence from a Genetic Analysis of the Fast Track Randomized Control Trial. (5th January 2015)

• Record Type: Journal Article
• Authors: Albert, Dustin; Belsky, Daniel W.; Crowley, D. Max; Latendresse, Shawn J.; Aliev, Fazil; Riley, Brien; Sun, Cuie; Conduct Problems Prevention Research Group; Dick, Danielle M.; Dodge, Kenneth A.
• Is Part Of: Journal of policy analysis and management. Volume 34:issue 3(2015)
• Page Start: 497
• Page End: 518
• Publication Date: 2015-01-05
• Subjects: Policy sciences -- Periodicals; Political planning -- United States -- Periodicals; United States -- Social policy -- Periodicals; 353
• DOI: 10.1002/pam.21811
• Languages: English
• ISSNs: 0276-8739

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Early interventions are a preferred method for addressing behavioral problems in high‐risk children, but often have only modest effects. Identifying sources of variation in intervention effects can suggest means to improve efficiency. One potential source of such variation is the genome. We conducted a genetic analysis of the Fast Track randomized control trial, a 10‐year‐long intervention to prevent high‐risk kindergarteners from developing adult externalizing problems including substance abuse and antisocial behavior. We tested whether variants of the glucocorticoid receptor gene NR3C1 were associated with differences in response to the Fast Track intervention. We found that in European‐American children, a variant of NR3C1 identified by the single‐nucleotide polymorphism rs10482672 was associated with increased risk for externalizing psychopathology in control group children and decreased risk for externalizing psychopathology in intervention group children. Variation in NR3C1 measured in this study was not associated with differential intervention response in African‐American children. We discuss implications for efforts to prevent externalizing problems in high‐risk children and for public policy in the genomic era.</p> </abstract>