High-Throughput Analysis of Calcium Signalling Kinetics in Astrocytes Stimulated with Different Neurotransmitters

Astrocytes express a wide range of receptors for neurotransmitters and hormones that are coupled to increases in intracellular Ca2+ concentration, enabling them to detect activity in both neuronal and vascular networks. There is increasing evidence that astrocytes are able to discriminate between different Ca2+-linked stimuli, as the efficiency of some Ca2+ dependent processes – notably release of gliotransmitters – depends on the stimulus that initiates the Ca2+ signal. The spatiotemporal complexity of Ca2+ signals is substantial, and we here tested the hypothesis that variation in the kinetics of Ca2+ responses could offer a means of selectively engaging downstream targets, if agonists exhibited a “signature shape” in evoked Ca2+ response. To test this, astrocytes were exposed to three different receptor agonists (ATP, glutamate and histamine) and the resultant Ca2+ signals were analysed for systematic differences in kinetics that depended on the initiating stimulus. We found substantial heterogeneity between cells in the time course of Ca2+ responses, but the variation did not correlate with the type or concentration of the stimulus. Using a simple metric to quantify the extent of difference between populations, it was found that the variation between agonists was insufficient to allow signal discrimination. We conclude that the time course of global intracellular Ca2+ signals does not offer the cells a means for distinguishing between different neurotransmitters

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.Peer reviewe