Towards the clinical implementation of pharmacogenetics in bipolar disorder.

BackgroundBipolar disorder (BD) is a psychiatric illness defined by pathological alterations between the mood states of mania and depression, causing disability, imposing healthcare costs and elevating the risk of suicide. Although effective treatments for BD exist, variability in outcomes leads to a large number of treatment failures, typically followed by a trial and error process of medication switches that can take years. Pharmacogenetic testing (PGT), by tailoring drug choice to an individual, may personalize and expedite treatment so as to identify more rapidly medications well suited to individual BD patients.DiscussionA number of associations have been made in BD between medication response phenotypes and specific genetic markers. However, to date clinical adoption of PGT has been limited, often citing questions that must be answered before it can be widely utilized. These include: What are the requirements of supporting evidence? How large is a clinically relevant effect? What degree of specificity and sensitivity are required? Does a given marker influence decision making and have clinical utility? In many cases, the answers to these questions remain unknown, and ultimately, the question of whether PGT is valid and useful must be determined empirically. Towards this aim, we have reviewed the literature and selected drug-genotype associations with the strongest evidence for utility in BD.SummaryBased upon these findings, we propose a preliminary panel for use in PGT, and a method by which the results of a PGT panel can be integrated for clinical interpretation. Finally, we argue that based on the sufficiency of accumulated evidence, PGT implementation studies are now warranted. We propose and discuss the design for a randomized clinical trial to test the use of PGT in the treatment of BD

Brand Suicide? Memory and Liking of Negative Brand Names

Negative brand names are surprisingly common in the marketplace (e.g., Poison perfume; Hell pizza, and Monster energy drink), yet their effects on consumer behavior are currently unknown. Three studies investigated the effects of negative brand name valence on brand name memory and liking of a branded product. Study 1 demonstrates that relative to nonnegative brand names, negative brand names and their associated logos are better recognised. Studies 2 and 3 demonstrate that negative valence of a brand name tends to have a detrimental influence on product evaluation with evaluations worsening as negative valence increases. However, evaluation is also dependent on brand name arousal, with high arousal brand names resulting in more positive evaluations, such that moderately negative brand names are equally as attractive as some non-negative brand names. Study 3 shows evidence for affective habituation, whereby the effects of negative valence reduce with repeated exposures to some classes of negative brand name

Measurement of the top quark mass using the matrix element technique in dilepton final states

We present a measurement of the top quark mass in pp¯ collisions at a center-of-mass energy of 1.96 TeV at the Fermilab Tevatron collider. The data were collected by the D0 experiment corresponding to an integrated luminosity of 9.7  fb−1. The matrix element technique is applied to tt¯ events in the final state containing leptons (electrons or muons) with high transverse momenta and at least two jets. The calibration of the jet energy scale determined in the lepton+jets final state of tt¯ decays is applied to jet energies. This correction provides a substantial reduction in systematic uncertainties. We obtain a top quark mass of mt=173.93±1.84  GeV

Ratio of the Isolated Photon Cross Sections at \sqrt{s} = 630 and 1800 GeV

The inclusive cross section for production of isolated photons has been measured in \pbarp collisions at $\sqrt{s} = 630$ GeV with the \D0 detector at the Fermilab Tevatron Collider. The photons span a transverse energy ($E_T$) range from 7-49 GeV and have pseudorapidity $|\eta| < 2.5$. This measurement is combined with to previous \D0 result at $\sqrt{s} = 1800$ GeV to form a ratio of the cross sections. Comparison of next-to-leading order QCD with the measured cross section at 630 GeV and ratio of cross sections show satisfactory agreement in most of the $E_T$ range.Comment: 7 pages. Published in Phys. Rev. Lett. 87, 251805, (2001

Multi-locus genome-wide association analysis supports the role of glutamatergic synaptic transmission in the etiology of major depressive disorder

Major depressive disorder (MDD) is a common psychiatric illness characterized by low mood and loss of interest in pleasurable activities. Despite years of effort, recent genome-wide association studies (GWAS) have identified few susceptibility variants or genes that are robustly associated with MDD. Standard single-SNP (single nucleotide polymorphism)-based GWAS analysis typically has limited power to deal with the extensive heterogeneity and substantial polygenic contribution of individually weak genetic effects underlying the pathogenesis of MDD. Here, we report an alternative, gene-set-based association analysis of MDD in an effort to identify groups of biologically related genetic variants that are involved in the same molecular function or cellular processes and exhibit a significant level of aggregated association with MDD. In particular, we used a text-mining-based data analysis to prioritize candidate gene sets implicated in MDD and conducted a multi-locus association analysis to look for enriched signals of nominally associated MDD susceptibility loci within each of the gene sets. Our primary analysis is based on the meta-analysis of three large MDD GWAS data sets (total N = 4346 cases and 4430 controls). After correction for multiple testing, we found that genes involved in glutamatergic synaptic neurotransmission were significantly associated with MDD (set-based association P = 6.9 X 10(-4)). This result is consistent with previous studies that support a role of the glutamatergic system in synaptic plasticity and MDD and support the potential utility of targeting glutamatergic neurotransmission in the treatment of MDD

Engineering the surface properties of a human monoclonal antibody prevents self-association and rapid clearance in vivo

Uncontrolled self-association is a major challenge in the exploitation of proteins as therapeutics. Here we describe the development of a structural proteomics approach to identify the amino acids responsible for aberrant self-association of monoclonal antibodies and the design of a variant with reduced aggregation and increased serum persistence in vivo. We show that the human monoclonal antibody, MEDI1912, selected against nerve growth factor binds with picomolar affinity, but undergoes reversible self-association and has a poor pharmacokinetic profile in both rat and cynomolgus monkeys. Using hydrogen/deuterium exchange and cross-linking-mass spectrometry we map the residues responsible for self-association of MEDI1912 and show that disruption of the self-interaction interface by three mutations enhances its biophysical properties and serum persistence, whilst maintaining high affinity and potency. Immunohistochemistry suggests that this is achieved via reduction of non-specific tissue binding. The strategy developed represents a powerful and generic approach to improve the properties of therapeutic proteins

Comparative Lipidomics of Azole Sensitive and Resistant Clinical Isolates of Candida albicans Reveals Unexpected Diversity in Molecular Lipid Imprints

Although transcriptome and proteome approaches have been applied to determine the regulatory circuitry behind multidrug resistance (MDR) in Candida, its lipidome remains poorly characterized. Lipids do acclimatize to the development of MDR in Candida, but exactly how the acclimatization is achieved is poorly understood. In the present study, we have used a high-throughput mass spectrometry-based shotgun approach and analyzed the lipidome of genetically matched clinical azole-sensitive (AS) and -resistant (AR) isolates of C. albicans. By comparing the lipid profiling of matched isolates, we have identified major classes of lipids and determined more than 200 individual molecular lipid species among these major classes. The lipidome analysis has been statistically validated by principal component analysis. Although each AR isolate was similar with regard to displaying a high MIC to drugs, they had a distinct lipid imprint. There were some significant commonalities in the lipid profiles of these pairs, including molecular lipid species ranging from monounsaturated to polyunsaturated fatty acid-containing phosphoglycerides. Consistent fluctuation in phosphatidyl serine, mannosylinositolphosphorylceramides, and sterol esters levels indicated their compensatory role in maintaining lipid homeostasis among most AR isolates. Notably, overexpression of either CaCdr1p or CaMdr1p efflux pump proteins led to a different lipidomic response among AR isolates. This study clearly establishes the versatility of lipid metabolism in handling azole stress among various matched AR isolates. This comprehensive lipidomic approach will serve as a resource for assessing strategies aimed at disrupting the functions of Candida lipids, particularly the functional interactions between lipids and MDR determinants

Common Variants of Inflammatory Cytokine Genes Are Associated with Risk of Nephropathy in Type 2 Diabetes among Asian Indians

BACKGROUND: Inflammatory cytokine genes have been proposed as good candidate genes for conferring susceptibility to diabetic nephropathy. In the present study, we examined the combined effect of multiple alleles of pro inflammatory cytokine genes for determining the risk of nephropathy in type 2 diabetic patients. METHODOLOGY/PRINCIPAL FINDINGS: Eight single nucleotide polymorphisms (SNPs) of pro-inflammatory cytokine genes (CCL2, TGFB1, IL8, CCR5, and MMP9) were genotyped in two independently ascertained type 2 diabetic cohorts with (DN) and without nephropathy (DM); consisting of patients from North India (n = 495) and South India (n = 188). Genotyping was carried out using PCR, allele specific oligonucleotide-PCR (ASO-PCR), PCR-RFLP and TaqMan allelic discrimination assays and the gene-gene interaction among genetic variants were determined by multi dimensional reduction (MDR) software. Serum high sensitive CRP (hs-CRP) levels were measured by ELISA. The hs-CRP levels were significantly higher in DN as compared to the DM group (p<0.05). The CCL2, IL8, CCR5 and MMP9 polymorphisms were found to be associated with the risk of diabetic nephropathy. Frequency of CCL2 II, IL8 -251AA, CCR5 59029AA and MMP9 279Gln/Gln genotypes were significantly higher in DN than in DM group (p<0.05) and associated with an increased risk of nephropathy in both North and South Indian cohorts. CCR5 DD and IL8 -251AA genotypes were more prevalent in North Indian DN group only. The co-occurrence of risk associated genotypes (II, -2518GG (CCL2), DD (CCR5) and 279Gln/Gln (MMP9) conferred a tenfold increased risk of nephropathy among type 2 diabetics (p<0.0002). CONCLUSION: The present study highlights that common variants of inflammatory cytokine genes exert a modest effect on risk of DN and a combination of risk alleles confer a substantial increased risk of nephropathy in type 2 diabetes among Asian Indians