A Genome-Wide Investigation of SNPs and CNVs in Schizophrenia

We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater “load” of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens

Actinide covalency measured by pulsed electron paramagnetic resonance spectroscopy

Our knowledge of actinide chemical bonds lags far behind our understanding of the bonding regimes of any other series of elements. This is a major issue given the technological as well as fundamental importance of f-block elements. Some key chemical differences between actinides and lanthanides—and between different actinides—can be ascribed to minor differences in covalency, that is, the degree to which electrons are shared between the f-block element and coordinated ligands. Yet there are almost no direct measures of such covalency for actinides. Here we report the first pulsed electron paramagnetic resonance spectra of actinide compounds. We apply the hyperfine sublevel correlation technique to quantify the electron-spin density at ligand nuclei (via the weak hyperfine interactions) in molecular thorium(III) and uranium(III) species and therefore the extent of covalency. Such information will be important in developing our understanding of the chemical bonding, and therefore the reactivity, of actinides

Congruence of tissue expression profiles from Gene Expression Atlas, SAGEmap and TissueInfo databases

BACKGROUND: Extracting biological knowledge from large amounts of gene expression information deposited in public databases is a major challenge of the postgenomic era. Additional insights may be derived by data integration and cross-platform comparisons of expression profiles. However, database meta-analysis is complicated by differences in experimental technologies, data post-processing, database formats, and inconsistent gene and sample annotation. RESULTS: We have analysed expression profiles from three public databases: Gene Expression Atlas, SAGEmap and TissueInfo. These are repositories of oligonucleotide microarray, Serial Analysis of Gene Expression and Expressed Sequence Tag human gene expression data respectively. We devised a method, Preferential Expression Measure, to identify genes that are significantly over- or under-expressed in any given tissue. We examined intra- and inter-database consistency of Preferential Expression Measures. There was good correlation between replicate experiments of oligonucleotide microarray data, but there was less coherence in expression profiles as measured by Serial Analysis of Gene Expression and Expressed Sequence Tag counts. We investigated inter-database correlations for six tissue categories, for which data were present in the three databases. Significant positive correlations were found for brain, prostate and vascular endothelium but not for ovary, kidney, and pancreas. CONCLUSION: We show that data from Gene Expression Atlas, SAGEmap and TissueInfo can be integrated using the UniGene gene index, and that expression profiles correlate relatively well when large numbers of tags are available or when tissue cellular composition is simple. Finally, in the case of brain, we demonstrate that when PEM values show good correlation, predictions of tissue-specific expression based on integrated data are very accurate

Dementia Revealed: Novel Chromosome 6 Locus for Late-Onset Alzheimer Disease Provides Genetic Evidence for Folate-Pathway Abnormalities

Genome-wide association studies (GWAS) of late-onset Alzheimer disease (LOAD) have consistently observed strong evidence of association with polymorphisms in APOE. However, until recently, variants at few other loci with statistically significant associations have replicated across studies. The present study combines data on 483,399 single nucleotide polymorphisms (SNPs) from a previously reported GWAS of 492 LOAD cases and 496 controls and from an independent set of 439 LOAD cases and 608 controls to strengthen power to identify novel genetic association signals. Associations exceeding the experiment-wide significance threshold () were replicated in an additional 1,338 cases and 2,003 controls. As expected, these analyses unequivocally confirmed APOE's risk effect (rs2075650, ). Additionally, the SNP rs11754661 at 151.2 Mb of chromosome 6q25.1 in the gene MTHFD1L (which encodes the methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 1-like protein) was significantly associated with LOAD (; Bonferroni-corrected P = 0.022). Subsequent genotyping of SNPs in high linkage disequilibrium () with rs11754661 identified statistically significant associations in multiple SNPs (rs803424, P = 0.016; rs2073067, P = 0.03; rs2072064, P = 0.035), reducing the likelihood of association due to genotyping error. In the replication case-control set, we observed an association of rs11754661 in the same direction as the previous association at P = 0.002 ( in combined analysis of discovery and replication sets), with associations of similar statistical significance at several adjacent SNPs (rs17349743, P = 0.005; rs803422, P = 0.004). In summary, we observed and replicated a novel statistically significant association in MTHFD1L, a gene involved in the tetrahydrofolate synthesis pathway. This finding is noteworthy, as MTHFD1L may play a role in the generation of methionine from homocysteine and influence homocysteine-related pathways and as levels of homocysteine are a significant risk factor for LOAD development

Are the associations between Alzheimer\u27s disease and polymorphisms in the apolipoprotein E and the apolipoprotein CII genes due to linkage disequilibrium

Allele frequencies for polymorphisms in the apolipoprotein E and the apolipoprotein CII genes were determined in subjects of Ashkenazi Jewish origin with late-onset Alzheimer\u27s disease and in unaffected control subjects from the same ethnic group. A significant association was observed between late-onset Alzheimer\u27s disease and the epsilon 4 (112Cys--\u3eArg) allele of apolipoprotein E; however, no association was detected with apolipoprotein CII. These results suggest that the association with epsilon 4 is probably not due to linkage disequilibrium