Mouse and human genetic analyses associate kalirin with ventral striatal activation during impulsivity and with alcohol misuse
Frontiers in genetics, 7, 52, 2016
Abstract: Impulsivity is associated with a spectrum of psychiatric disorders including drug addiction. To investigate genetic associations with impulsivity and initiation of drug taking, we took a two-step approach. First, we identified genes whose expression level in prefrontal cortex, striatum and accumbens were associated with impulsive behavior in the 5-choice serial reaction time task across 10 BXD recombinant inbred (BXD RI) mouse strains and their progenitor C57BL/6J and DBA2/J strains. Behavioral data were correlated with regional gene expression using GeneNetwork (www.genenetwork.org), to identify 44 genes whose probability of association with impulsivity exceeded a false discovery rate of < 0.05. We then interrogated the IMAGEN database of 1423 adolescents for potential associations of SNPs in human homologs of those genes identified in the mouse study, with brain activation during impulsive performance in the Monetary Incentive Delay task, and with novelty seeking scores from the Temperament and Character Inventory, as well as alcohol experience. There was a significant overall association between the human homologs of impulsivity-related genes and percentage of premature responses in the MID task and with fMRI BOLD-response in ventral striatum (VS) during reward anticipation. In contrast, no significant association was found between the polygenic scores and anterior cingulate cortex activation. Univariate association analyses revealed that the G allele (major) of the intronic SNP rs6438839 in the KALRN gene was significantly associated with increased VS activation. Additionally, the A-allele (minor) of KALRN intronic SNP rs4634050, belonging to the same haplotype block, was associated with increased frequency of binge drinking.
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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).