Reducing ion channel activity in a series of 4-heterocyclic arylamide FMS inhibitors

During efforts to improve the bioavailability of FMS kinase inhibitors 1 and 2, a series of saturated and aromatic 4-heterocycles of reduced basicity were prepared and evaluated in an attempt to also improve the cardiovascular safety profile over lead arylamide 1, which possessed ion channel activity. The resultant compounds retained excellent potency and exhibited diminished ion channel activity.     

Blood cis-eQTL Analysis Fails to Identify Novel Association Signals among Sub-Threshold Candidates from Genome-Wide Association Studies in Restless Legs Syndrome

Restless legs syndrome (RLS) is a common neurologic disorder characterized by nightly dysesthesias affecting the legs primarily during periods of rest and relieved by movement. RLS is a complex genetic disease and susceptibility factors in six genomic regions have been identified by means of genome-wide association studies (GWAS). For some complex genetic traits, expression quantitative trait loci (eQTLs) are enriched among trait-associated single nucleotide polymorphisms (SNPs). With the aim of identifying new genetic susceptibility factors for RLS, we assessed the 332 best-associated SNPs from the genome-wide phase of the to date largest RLS GWAS for cis-eQTL effects in peripheral blood from individuals of European descent. In 740 individuals belonging to the KORA general population cohort, 52 cis-eQTLs with p_nominal<10⁻³ were identified, while in 976 individuals belonging to the SHIP-TREND general population study 53 cis-eQTLs with p_nominal<10⁻³ were present. 23 of these cis-eQTLs overlapped between the two cohorts. Subsequently, the twelve of the 23 cis-eQTL SNPs, which were not located at an already published RLS-associated locus, were tested for association in 2449 RLS cases and 1462 controls. The top SNP, located in the DET1 gene, was nominally significant (p<0.05) but did not withstand correction for multiple testing (p = 0.42). Although a similar approach has been used successfully with regard to other complex diseases, we were unable to identify new genetic susceptibility factor for RLS by adding this novel level of functional assessment to RLS GWAS data.     

Targeted metabolomics profiles are strongly correlated with nutritional patterns in women

Nutrition plays an important role in human metabolism and health. Metabolomics is a promising tool for clinical, genetic and nutritional studies. A key question is to what extent metabolomic profiles reflect nutritional patterns in an epidemiological setting. We assessed the relationship between metabolomic profiles and nutritional intake in women from a large cross-sectional community study. Food frequency questionnaires (FFQs) were applied to 1,003 women from the TwinsUK cohort with targeted metabolomic analyses of serum samples using the Biocrates Absolute-IDQ? Kit p150 (163 metabolites). We analyzed seven nutritional parameters: coffee intake, garlic intake and nutritional scores derived from the FFQs summarizing fruit and vegetable intake, alcohol intake, meat intake, hypo-caloric dieting and a “traditional English” diet. We studied the correlation between metabolite levels and dietary intake patterns in the larger population and identified for each trait between 14 and 20 independent monozygotic twins pairs discordant for nutritional intake and replicated results in this set. Results from both analyses were then meta-analyzed. For the metabolites associated with nutritional patterns, we calculated heritability using structural equation modelling. 42 metabolite nutrient intake associations were statistically significant in the discovery samples (Bonferroni P < 4 × 10^?5) and 11 metabolite nutrient intake associations remained significant after validation. We found the strongest associations for fruit and vegetables intake and a glycerophospholipid (Phosphatidylcholine diacyl C38:6, P = 1.39 × 10^?9) and a sphingolipid (Sphingomyeline C26:1, P = 6.95 × 10^?13). We also found significant associations for coffee (confirming a previous association with C10 reported in an independent study), garlic intake and hypo-caloric dieting. Using the twin study design we find that two thirds the metabolites associated with nutritional patterns have a significant genetic contribution, and the remaining third are solely environmentally determined. Our data confirm the value of metabolomic studies for nutritional epidemiologic research.     

Structure-activity and crystallographic analysis of a new class of non-amide-based thrombin inhibitor

The structure activity relationships of a novel series of non-amide-based thrombin inhibitors are described. Exploration of the P2 and the aryl binding region for this series has identified optimal groups for achieving nanomolar potency. The binding modes of these optimal groups have been confirmed by X-ray structural analysis.     

Structure-based optimization of a potent class of arylamide FMS inhibitors

An anti-inflammatory 1,2,4-phenylenetriamine-containing series of FMS inhibitors with a potential to form reactive metabolites was transformed into a series with equivalent potency by incorporation of carbon-based replacement groups. Structure-based modeling provided the framework to efficiently effect this transformation and restore potencies to previous levels. This optimization removed a risk factor for potential idiosyncratic drug reactions.     

Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data

Background  

With the advent of high-throughput targeted metabolic profiling techniques, the question of how to interpret and analyze the resulting vast amount of data becomes more and more important. In this work we address the reconstruction of metabolic reactions from cross-sectional metabolomics data, that is without the requirement for time-resolved measurements or specific system perturbations. Previous studies in this area mainly focused on Pearson correlation coefficients, which however are generally incapable of distinguishing between direct and indirect metabolic interactions.     

Common Polymorphisms Influencing Serum Uric Acid Levels Contribute to Susceptibility to Gout,but Not to Coronary Artery Disease

Background

Recently, a large meta-analysis including over 28,000 participants identified nine different loci with association to serum uric acid (UA) levels. Since elevated serum UA levels potentially cause gout and are a possible risk factor for coronary artery disease (CAD) and myocardial infarction (MI), we performed two large case-control association analyses with participants from the German MI Family Study. In the first study, we assessed the association of the qualitative trait gout and ten single nucleotide polymorphisms (SNP) markers that showed association to UA serum levels. In the second study, the same genetic polymorphisms were analyzed for association with CAD.

Methods and Findings

A total of 683 patients suffering from gout and 1,563 healthy controls from the German MI Family Study were genotyped. Nine SNPs were identified from a recently performed genome-wide meta-analysis on serum UA levels (rs12129861, rs780094, rs734553, rs2231142, rs742132, rs1183201, rs12356193, rs17300741 and rs505802). Additionally, the marker rs6855911 was included which has been associated with gout in our cohort in a previous study. SNPs rs734553 and rs6855911, located in SLC2A9, and SNP rs2231142, known to be a missense polymorphism in ABCG2, were associated with gout (p = 5.6*10⁻⁷, p = 1.1*10⁻⁷, and p = 1.3*10⁻³, respectively). Other SNPs in the genes PDZK1, GCKR, LRRC16A, SLC17A1-SLC17A3, SLC16A9, SLC22A11 and SLC22A12 failed the significance level. None of the ten markers were associated with risk to CAD in our study sample of 1,473 CAD cases and 1,241 CAD-free controls.

Conclusion

SNP markers in SLC2A9 and ABCG2 genes were found to be strongly associated with the phenotype gout. However, not all SNP markers influencing serum UA levels were also directly associated with the clinical manifestation of gout in our study sample. In addition, none of these SNPs showed association with the risk to CAD in the German MI Family Study.