Whole-genome association analysis of treatment response in obsessive-compulsive disorder.

Up to 30% of patients with obsessive-compulsive disorder (OCD) exhibit an inadequate response to serotonin reuptake inhibitors (SRIs). To date, genetic predictors of OCD treatment response have not been systematically investigated using genome-wide association study (GWAS). To identify specific genetic variations potentially influencing SRI response, we conducted a GWAS study in 804 OCD patients with information on SRI response. SRI response was classified as 'response' (n=514) or 'non-response' (n=290), based on self-report. We used the more powerful Quasi-Likelihood Score Test (the MQLS test) to conduct a genome-wide association test correcting for relatedness, and then used an adjusted logistic model to evaluate the effect size of the variants in probands. The top single-nucleotide polymorphism (SNP) was rs17162912 (P=1.76 × 10(-8)), which is near the DISP1 gene on 1q41-q42, a microdeletion region implicated in neurological development. The other six SNPs showing suggestive evidence of association (P<10(-5)) were rs9303380, rs12437601, rs16988159, rs7676822, rs1911877 and rs723815. Among them, two SNPs in strong linkage disequilibrium, rs7676822 and rs1911877, located near the PCDH10 gene, gave P-values of 2.86 × 10(-6) and 8.41 × 10(-6), respectively. The other 35 variations with signals of potential significance (P<10(-4)) involve multiple genes expressed in the brain, including GRIN2B, PCDH10 and GPC6. Our enrichment analysis indicated suggestive roles of genes in the glutamatergic neurotransmission system (false discovery rate (FDR)=0.0097) and the serotonergic system (FDR=0.0213). Although the results presented may provide new insights into genetic mechanisms underlying treatment response in OCD, studies with larger sample sizes and detailed information on drug dosage and treatment duration are needed

Genome-wide association study in obsessive-compulsive disorder: results from the OCGAS.

Obsessive-compulsive disorder (OCD) is a psychiatric condition characterized by intrusive thoughts and urges and repetitive, intentional behaviors that cause significant distress and impair functioning. The OCD Collaborative Genetics Association Study (OCGAS) is comprised of comprehensively assessed OCD patients with an early age of OCD onset. After application of a stringent quality control protocol, a total of 1065 families (containing 1406 patients with OCD), combined with population-based samples (resulting in a total sample of 5061 individuals), were studied. An integrative analyses pipeline was utilized, involving association testing at single-nucleotide polymorphism (SNP) and gene levels (via a hybrid approach that allowed for combined analyses of the family- and population-based data). The smallest P-value was observed for a marker on chromosome 9 (near PTPRD, P=4.13 × 10(-)(7)). Pre-synaptic PTPRD promotes the differentiation of glutamatergic synapses and interacts with SLITRK3. Together, both proteins selectively regulate the development of inhibitory GABAergic synapses. Although no SNPs were identified as associated with OCD at genome-wide significance level, follow-up analyses of genome-wide association study (GWAS) signals from a previously published OCD study identified significant enrichment (P=0.0176). Secondary analyses of high-confidence interaction partners of DLGAP1 and GRIK2 (both showing evidence for association in our follow-up and the original GWAS study) revealed a trend of association (P=0.075) for a set of genes such as NEUROD6, SV2A, GRIA4, SLC1A2 and PTPRD. Analyses at the gene level revealed association of IQCK and C16orf88 (both P<1 × 10(-)(6), experiment-wide significant), as well as OFCC1 (P=6.29 × 10(-)(5)). The suggestive findings in this study await replication in larger samples

Use of linear mixed models for genetic evaluation of gestation length and birth weight allowing for heavy-tailed residual effects

<p>Abstract</p> <p>Background</p> <p>The distribution of residual effects in linear mixed models in animal breeding applications is typically assumed normal, which makes inferences vulnerable to outlier observations. In order to mute the impact of outliers, one option is to fit models with residuals having a heavy-tailed distribution. Here, a Student's-<it>t </it>model was considered for the distribution of the residuals with the degrees of freedom treated as unknown. Bayesian inference was used to investigate a bivariate Student's-<it>t </it>(BS<it>t</it>) model using Markov chain Monte Carlo methods in a simulation study and analysing field data for gestation length and birth weight permitted to study the practical implications of fitting heavy-tailed distributions for residuals in linear mixed models.</p> <p>Methods</p> <p>In the simulation study, bivariate residuals were generated using Student's-<it>t </it>distribution with 4 or 12 degrees of freedom, or a normal distribution. Sire models with bivariate Student's-<it>t </it>or normal residuals were fitted to each simulated dataset using a hierarchical Bayesian approach. For the field data, consisting of gestation length and birth weight records on 7,883 Italian Piemontese cattle, a sire-maternal grandsire model including fixed effects of sex-age of dam and uncorrelated random herd-year-season effects were fitted using a hierarchical Bayesian approach. Residuals were defined to follow bivariate normal or Student's-<it>t </it>distributions with unknown degrees of freedom.</p> <p>Results</p> <p>Posterior mean estimates of degrees of freedom parameters seemed to be accurate and unbiased in the simulation study. Estimates of sire and herd variances were similar, if not identical, across fitted models. In the field data, there was strong support based on predictive log-likelihood values for the Student's-<it>t </it>error model. Most of the posterior density for degrees of freedom was below 4. Posterior means of direct and maternal heritabilities for birth weight were smaller in the Student's-<it>t </it>model than those in the normal model. Re-rankings of sires were observed between heavy-tailed and normal models.</p> <p>Conclusions</p> <p>Reliable estimates of degrees of freedom were obtained in all simulated heavy-tailed and normal datasets. The predictive log-likelihood was able to distinguish the correct model among the models fitted to heavy-tailed datasets. There was no disadvantage of fitting a heavy-tailed model when the true model was normal. Predictive log-likelihood values indicated that heavy-tailed models with low degrees of freedom values fitted gestation length and birth weight data better than a model with normally distributed residuals.</p> <p>Heavy-tailed and normal models resulted in different estimates of direct and maternal heritabilities, and different sire rankings. Heavy-tailed models may be more appropriate for reliable estimation of genetic parameters from field data.</p

Design and feasibility testing of a novel group intervention for young women who binge drink in groups

BackgroundYoung women frequently drink alcohol in groups and binge drinking within these natural drinking groups is common. This study describes the design of a theoretically and empirically based group intervention to reduce binge drinking among young women. It also evaluates their engagement with the intervention and the acceptability of the study methods.MethodsFriendship groups of women aged 18–35 years, who had two or more episodes of binge drinking (>6 UK units on one occasion; 48g of alcohol) in the previous 30 days, were recruited from the community. A face-to-face group intervention, based on the Health Action Process Approach, was delivered over three sessions. Components of the intervention were woven around fun activities, such as making alcohol free cocktails. Women were followed up four months after the intervention was delivered. Results The target of 24 groups (comprising 97 women) was recruited. The common pattern of drinking was infrequent, heavy drinking (mean consumption on the heaviest drinking day was UK 18.1 units). Process evaluation revealed that the intervention was delivered with high fidelity and acceptability of the study methods was high. The women engaged positively with intervention components and made group decisions about cutting down. Twenty two groups set goals to reduce their drinking, and these were translated into action plans. Retention of individuals at follow up was 87%.ConclusionsThis study successfully recruited groups of young women whose patterns of drinking place them at high risk of acute harm. This novel approach to delivering an alcohol intervention has potential to reduce binge drinking among young women. The high levels of engagement with key steps in the behavior change process suggests that the group intervention should be tested in a full randomised controlled trial

Phenotypic Variation and Bistable Switching in Bacteria

Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.

Antenna-coupled TES bolometers for the SPIDER experiment

SPIDER is a proposed balloon-borne experiment designed to search for the imprints of gravity waves on the polarization of the cosmic microwave background radiation. The required wide frequency coverage, large number of sensitive detectors, and the stringent power constraints on a balloon are made possible by antenna-coupled TES bolometers. Several prototype devices have been fabricated and optically characterized. Their spectral and angular responses agree well with the theoretical expectations

Cosmogenic neutron production at the Sudbury Neutrino Observatory

Neutrons produced in nuclear interactions initiated by cosmic-ray muons present an irreducible background to many rare-event searches, even in detectors located deep underground. Models for the production of these neutrons have been tested against previous experimental data, but the extrapolation to deeper sites is not well understood. Here we report results from an analysis of cosmogenically produced neutrons at the Sudbury Neutrino Observatory. A specific set of observables are presented, which can be used to benchmark the validity of geant4 physics models. In addition, the cosmogenic neutron yield, in units of 10-4 cm2/(g·μ), is measured to be 7.28±0.09(stat)-1.12+1.59(syst) in pure heavy water and 7.30±0.07(stat)-1.02+1.40(syst) in NaCl-loaded heavy water. These results provide unique insights into this potential background source for experiments at SNOLAB

Fractional deuteration applied to biomolecular solid-state NMR spectroscopy

Solid-state Nuclear Magnetic Resonance can provide detailed insight into structural and dynamical aspects of complex biomolecules. With increasing molecular size, advanced approaches for spectral simplification and the detection of medium to long-range contacts become of critical relevance. We have analyzed the protonation pattern of a membrane-embedded ion channel that was obtained from bacterial expression using protonated precursors and D2O medium. We find an overall reduction of 50% in protein protonation. High levels of deuteration at Hα and Hβ positions reduce spectral congestion in (1H,13C,15N) correlation experiments and generate a transfer profile in longitudinal mixing schemes that can be tuned to specific resonance frequencies. At the same time, residual protons are predominantly found at amino-acid side-chain positions enhancing the prospects for obtaining side-chain resonance assignments and for detecting medium to long-range contacts. Fractional deuteration thus provides a powerful means to aid the structural analysis of complex biomolecules by solid-state NMR