Impact of a Common Genetic Variation Associated With Putamen Volume on Neural Mechanisms of Attention-Deficit/Hyperactivity Disorder
Journal of the American Academy of Child & Adolescent Psychiatry, 56, 436-444, 2017
In a recent genomewide association study of subcortical brain volumes, a common genetic variation at rs945270 was identified as having the strongest effect on putamen volume, a brain measurement linked to familial risk for attention-deficit/hyperactivity disorder (ADHD). To determine whether rs945270 might be a genetic determinant of ADHD, its effects on ADHD-related symptoms and neural mechanisms of ADHD, such as response inhibition and reward sensitivity, were explored.
A large population sample of 1,834 14-year-old adolescents was used to test the effects of rs945270 on ADHD symptoms assessed through the Strengths and Difficulties Questionnaire and region-of-interest analyses of putamen activation by functional magnetic resonance imaging using the stop signal and monetary incentive delay tasks, assessing response inhibition and reward sensitivity, respectively.
There was a significant link between rs945270 and ADHD symptom scores, with the C allele associated with lower symptom scores, most notably hyperactivity. In addition, there were sex-specific effects of this variant on the brain. In boys, the C allele was associated with lower putamen activity during successful response inhibition, a brain response that was not associated with ADHD symptoms. In girls, putamen activation during reward anticipation increased with the number of C alleles, most significantly in the right putamen. Remarkably, right putamen activation during reward anticipation tended to negatively correlate with ADHD symptoms.
These results indicate that rs945270 might contribute to the genetic risk of ADHD partly through its effects on hyperactivity and reward processing in girls.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).