Changes in presynaptic calcium signalling accompany age‐related deficits in hippocampal LTP and cognitive impairment

The loss of cognitive function accompanying healthy aging is not associated with extensive or characteristic patterns of cell death, suggesting it is caused by more subtle changes in synaptic properties. In the hippocampal CA1 region, long‐term potentiation requires stronger stimulation for induction in aged rats and mice and long‐term depression becomes more prevalent. An age‐dependent impairment of postsynaptic calcium homeostasis may underpin these effects. We have examined changes in presynaptic calcium signalling in aged mice using a transgenic mouse line (SyG37) that expresses a genetically encoded calcium sensor in presynaptic terminals. SyG37 mice showed an age‐dependent decline in cognitive abilities in behavioural tasks that require hippocampal processing including the Barnes maze, T‐maze and object location but not recognition tests. The incidence of LTP was significantly impaired in animals over 18 months of age. These effects of aging were accompanied by a persistent increase in resting presynaptic calcium, an increase in the presynaptic calcium signal following Schaffer collateral fibre stimulation, an increase in postsynaptic fEPSP slope and a reduction in paired‐pulse facilitation. These effects were not caused by synapse proliferation and were of presynaptic origin since they were evident in single presynaptic boutons. Aged synapses behaved like younger ones when the extracellular calcium concentration was reduced. Raising extracellular calcium had little effect on aged synapses but altered the properties of young synapses into those of their aged counterparts. These effects can be readily explained by an age‐dependent change in the properties or numbers of presynaptic calcium channels.     

A Protein Disulfide Isomerase Controls Neuronal Migration through Regulation of Wnt Secretion

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Proposed reporting requirements for the description of NMR-based metabolomics experiments

The amount of data generated by NMR-based metabolomic experiments is increasing rapidly. Furthermore, diverse techniques increase the need for informative and comprehensive meta-data. These factors present a challenge in the dissemination, interpretation, reviewing and comparison of experimental results using this technology. Thus, there is a strong case for unification and standardisation of the data representation for both academia and industry. Here, a systems analysis of an NMR-based metabolomics experiment is presented in order to reveal the reporting requirements. An in-depth analysis of the NMR component of a metabolomics experiment has been produced, and a first round of data standard development completed. This has focussed on both one- and two-dimensional ¹H NMR experiments, but is also applicable to higher dimensions and other nuclei. We also report the modelling of this schema using Unified Modelling Language (UML), and have extended this to a proof-of-concept implementation of the standard as an XML schema.     

Association between common variation in 120 candidate genes and breast cancer risk

Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran–Armitage trend test (p-trend) and a two-degrees of freedom χ² test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 × 10⁻⁵) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty.