Rabbit Anti-Human RASGRF2 (a.a. 748-876) Polyclonal antibody

Background The mesolimbic dopamine system, composed primarily of dopaminergic neurons in the ventral tegmental area that project to striatal structures, is considered to be the key mediator of reinforcement-related mechanisms in the brain. Prompted by a genome-wide association meta-analysis implicating the Ras-specific guanine nucleotide-releasing factor 2 (RASGRF2) gene in the regulation of alcohol intake in men, we have recently shown that male Rasgrf2(-/-) mice exhibit reduced ethanol intake and preference accompanied by a perturbed mesolimbic dopamine system. We therefore propose that these mice represent a valid model to further elucidate the precise genes and mechanisms regulating mesolimbic dopamine functioning. Methods Transcriptomic data from the nucleus accumbens (NAcc) of male Rasgrf2(-/-) mice and wild-type controls were analyzed by weighted gene coexpression network analysis (WGCNA). We performed follow-up genetic association tests in humans using a sample of male adolescents from the IMAGEN study characterized for binge drinking (n = 905) and ventral striatal activation during an fMRI reward task (n = 608). Results The WGCNA analyses using accumbal transcriptomic data revealed 37 distinct modules, or functionally related groups of genes. Two of these modules were significantly associated with Rasgrf2 knockout status: M5 (p < 0.001) and M6 (p < 0.001). In follow-up translational analyses we found that human orthologues for the M5 module were significantly (p < 0.01) enriched with genetic association signals for binge drinking in male adolescents. Furthermore, the most significant locus, originating from the EH-domain containing 4 (EHD4) gene (p < 0.001), was also significantly associated with altered ventral striatal activity in male adolescents performing an fMRI reward task (p(empirical) < 0.001). Limitations It was not possible to determine the extent to which the M5 module was dysregulated in Rasgrf2(-/-) mice by perturbed mesolimbic dopamine signalling or by the loss of Rasgrf2 function in the NAcc. Conclusion Taken together, our findings indicate that the accumbal M5 module, initially identified as being dysregulated in male Rasgrf2(-/-) mice, is also relevant for human alcohol-related phenotypes potentially through the modulation of reinforcement mechanisms in the NAcc. We therefore propose that the genes comprising this module represent important candidates for further elucidation within the context of alcohol-related phenotypes.

Several lines of evidence suggest that common polygenic variation influences brain function in humans. Combining high-density genetic markers with brain imaging techniques is constricted by the practicalities of collecting sufficiently large brain imaging samples. Pathway analysis promises to leverage knowledge on function of genes to detect recurring signals of moderate effect. We adapt this approach, exploiting the deep information collected on brain function by fMRI methods, to identify molecular pathways containing genetic variants which influence brain activation during a commonly applied experiment based on a face matching task (n = 246) which was developed to study neural processing of faces displaying negative emotions. Genetic markers moderately associated (p<10(-4)) with whole brain activation phenotypes constructed by applying principal components to contrast maps, were tested for pathway enrichment using permutation based methods. The most significant pathways are related to post NMDA receptor activation events, driven by genetic variants in calcium/calmodulin-dependent protein kinase II (CAMK2G, CAMK2D) and a calcium-regulated nucleotide exchange factor (RASGRF2) in which all are activated by intracellular calcium/calmodulin. The most significant effect of the combined polygenic model were localized to the left inferior frontal gyrus (p=1.03 x 10(-9)), a region primarily involved in semantic processing but also involved in processing negative emotions. These findings suggest that pathway analysis of GWAS results derived from principal component analysis of fMRI data is a promising method, to our knowledge, not previously described. (C) 2012 Elsevier Inc. All rights reserved.