Words Volume 1 2007-2009

https://openspace.dmacc.edu/words/1000/thumbnail.jp

Bicistronic Lentiviruses Containing a Viral 2A Cleavage Sequence Reliably Co-Express Two Proteins and Restore Vision to an Animal Model of LCA1

The disease processes underlying inherited retinal disease are complex and are not completely understood. Many of the corrective gene therapies designed to treat diseases linked to mutations in genes specifically expressed in photoreceptor cells restore function to these cells but fail to stop progression of the disease. There is growing consensus that effective treatments for these diseases will require delivery of multiple therapeutic proteins that will be selected to treat specific aspects of the disease process. The purpose of this study was to design a lentiviral transgene that reliably expresses all of the proteins it encodes and does so in a consistent manner among infected cells. We show, using both in vitro and in vivo analyses, that bicistronic lentiviral transgenes encoding two fluorescent proteins fused to a viral 2A-like cleavage peptide meet these expression criteria. To determine if this transgene design is suitable for therapeutic applications, we replaced one of the fluorescent protein genes with the gene encoding guanylate cyclase -1 (GC1) and delivered lentivirus carrying this transgene to the retinas of the GUCY1*B avian model of Leber congenital amaurosis – 1 (LCA1). GUCY1*B chickens carry a null mutation in the GC1 gene that disrupts photoreceptor function and causes blindness at hatching, a phenotype that closely matches that observed in humans with LCA1. We found that treatment of these animals with the 2A lentivector encoding GC1 restored vision to these animals as evidenced by the presence of optokinetic reflexes. We conclude that 2A-like peptides, with proper optimization, can be successfully incorporated into therapeutic vectors designed to deliver multiple proteins to neural retinal. These results highlight the potential of this vector design to serve as a platform for the development of combination therapies designed to enhance or prolong the benefits of corrective gene therapies

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function