Taok2 controls behavioral response to ethanol in mice

Despite recent advances in the understanding of ethanol's biological action, many of the molecular targets of ethanol and mechanisms behind ethanol's effect on behavior remain poorly understood. In an effort to identify novel genes, the products of which regulate behavioral responses to ethanol, we recently identified a mutation in the dtao gene that confers resistance to the locomotor stimulating effect of ethanol in Drosophila. dtao encodes a member of the Ste20 family of serine/threonine kinases implicated in MAP kinase signaling pathways. In this study, we report that conditional ablation of the mouse dtao homolog, Taok2, constitutively and specifically in the nervous system, results in strain‐specific and overlapping alterations in ethanol‐dependent behaviors. These data suggest a functional conservation of dtao and Taok2 in mediating ethanol's biological action and identify Taok2 as a putative candidate gene for ethanol use disorders in humans.     

Halogen bond tunability II: the varying roles of electrostatic and dispersion contributions to attraction in halogen bonds

In a previous study we investigated the effects of aromatic fluorine substitution on the strengths of the halogen bonds in halobenzene…acetone complexes (halo?=?chloro, bromo, and iodo). In this work, we have examined the origins of these halogen bonds (excluding the iodo systems), more specifically, the relative contributions of electrostatic and dispersion forces in these interactions and how these contributions change when halogen σ-holes are modified. These studies have been carried out using density functional symmetry adapted perturbation theory (DFT-SAPT) and through analyses of intermolecular correlation energies and molecular electrostatic potentials. It is found that electrostatic and dispersion contributions to attraction in halogen bonds vary from complex to complex, but are generally quite similar in magnitude. Not surprisingly, increasing the size and positive nature of a halogen’s σ-hole dramatically enhances the strength of the electrostatic component of the halogen bonding interaction. Not so obviously, halogens with larger, more positive σ-holes tend to exhibit weaker dispersion interactions, which is attributable to the lower local polarizabilities of the larger σ-holes.

Quantifying Missing Heritability at Known GWAS Loci

Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain more heritability than GWAS-associated SNPs on average (). For some diseases, this increase was individually significant: for Multiple Sclerosis (MS) () and for Crohn''s Disease (CD) (); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained more MS heritability than known MS SNPs () and more CD heritability than known CD SNPs (), with an analogous increase for all autoimmune diseases analyzed. We also observed significant increases in an analysis of Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with more heritability from all SNPs at GWAS loci () and more heritability from all autoimmune disease loci () compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.     

Patterns of time since last meal revealed by sparse PCA in an observational LC–MS based metabolomics study

In metabolomics studies, liquid chromatography mass spectrometry (LC–MS) provides comprehensive information on biological samples. However, extraction of few relevant metabolites from this large and complex data is cumbersome. To resolve this issue, we have employed sparse principal component analysis (SPCA) to capture the underlying patterns and select relevant metabolites from LC–MS plasma profiles. The study involves a small pilot cohort with 270 subjects where each subject’s time since last meal (TSLM) has been recorded prior to plasma sampling. Our results have demonstrated that both PCA and SPCA can capture the TSLM patterns. Nevertheless, SPCA provides more easily interpretable loadings in terms of selection of relevant metabolites, which are identified as amino acids and lyso-lipids. This study demonstrates the utility of SPCA as a pattern recognition and variable selection tool in metabolomics. Furthermore, amino acids and lyso-lipids are determined as dominating compounds in response to TSLM.