Interaction between effects of genes coding for dopamine and glutamate transmission on striatal and parahippocampal function

The genes for the dopamine transporter (DAT) and the D-Amino acid oxidase activator (DAOA or G72) have been independently implicated in the risk for schizophrenia and in bipolar disorder and/or their related intermediate phenotypes. DAT and G72 respectively modulate central dopamine and glutamate transmission, the two systems most robustly implicated in these disorders. Contemporary studies have demonstrated that elevated dopamine function is associated with glutamatergic dysfunction in psychotic disorders. Using functional magnetic resonance imaging we examined whether there was an interaction between the effects of genes that influence dopamine and glutamate transmission (DAT and G72) on regional brain activation during verbal fluency, which is known to be abnormal in psychosis, in 80 healthy volunteers. Significant interactions between the effects of G72 and DAT polymorphisms on activation were evident in the striatum, parahippocampal gyrus, and supramarginal/angular gyri bilaterally, the right insula, in the right pre-/postcentral and the left posterior cingulate/retrosplenial gyri (P < 0.05, FDR-corrected across the whole brain). This provides evidence that interactions between the dopamine and the glutamate system, thought to be altered in psychosis, have an impact in executive processing which can be modulated by common genetic variation.

Predictive Margins and Marginal Effects in Stata

Tables of estimated regression coefficients, usually accompanied by additional information such as standard errors, t-statistics, p-values, confidence intervals or significance stars, have long been the preferred way of communicating results from statistical models. In recent years, however, the limits of this form of exposition have been increasingly recognized. For example, interpretation of regression tables can be very challenging in the presence of complications such as interaction effects, categorical variables, or nonlinear functional forms. Furthermore, while these issues might still be manageable in the case of linear regression, interpretational difficulties can be overwhelming in nonlinear models such as logistic regression. To facilitate sensible interpretation of such models it is often necessary to compute additional results such as marginal effects, predictive margins, or contrasts. Moreover, smart graphical displays of results can be very valuable in making complex relations accessible. A number of helpful commands geared at supporting these tasks have been recently introduced in Stata, making elaborate interpretation and communication of regression results possible without much extra effort. Examples of such commands are -margins-, -contrasts-, and -marginsplot-. In my talk, I will discuss the capabilities of these commands and present a range of examples illustrating their use.

The long non-coding RNA NEAT1 is increased in IUGR placentas, leading to potential new hypotheses of IUGR origin/development.

INTRODUCTION Intrauterine Growth Restriction (IUGR) is a multifactorial disease defined by an inability of the fetus to reach its growth potential. IUGR not only increases the risk of neonatal mortality/morbidity, but also the risk of metabolic syndrome during adulthood. Certain placental proteins have been shown to be implicated in IUGR development, such as proteins from the GH/IGF axis and angiogenesis/apoptosis processes. METHODS Twelve patients with term IUGR pregnancy (birth weight < 10th percentile) and 12 CTRLs were included. mRNA was extracted from the fetal part of the placenta and submitted to a subtraction method (Clontech PCR-Select cDNA Subtraction). RESULTS One candidate gene identified was the long non-coding RNA NEAT1 (nuclear paraspeckle assembly transcript 1). NEAT1 is the core component of a subnuclear structure called paraspeckle. This structure is responsible for the retention of hyperedited mRNAs in the nucleus. Overall, NEAT1 mRNA expression was 4.14 (±1.16)-fold increased in IUGR vs. CTRL placentas (P = 0.009). NEAT1 was exclusively localized in the nuclei of the villous trophoblasts and was expressed in more nuclei and with greater intensity in IUGR placentas than in CTRLs. PSPC1, one of the three main proteins of the paraspeckle, co-localized with NEAT1 in the villous trophoblasts. The expression of NEAT1_2 mRNA, the long isoform of NEAT1, was only modestly increased in IUGR vs. CTRL placentas. DISCUSSION/CONCLUSION The increase in NEAT1 and its co-localization with PSPC1 suggests an increase in paraspeckles in IUGR villous trophoblasts. This could lead to an increased retention of important mRNAs in villous trophoblasts nuclei. Given that the villous trophoblasts are crucial for the barrier function of the placenta, this could in part explain placental dysfunction in idiopathic IUGR fetuses.

Predictive value of cerebrospinal fluid (CSF) lactate level versus CSF/blood glucose ratio for the diagnosis of bacterial meningitis following neurosurgery.

The value of cerebrospinal fluid (CSF) lactate level and CSF/blood glucose ratio for the identification of bacterial meningitis following neurosurgery was assessed in a retrospective study. During a 3-year period, 73 patients fulfilled the inclusion criteria and could be grouped by preset criteria in one of three categories: proven bacterial meningitis (n = 12), presumed bacterial meningitis (n = 14), and nonbacterial meningeal syndrome (n = 47). Of 73 patients analyzed, 45% were treated with antibiotics and 33% with steroids at the time of first lumbar puncture. CSF lactate values (cutoff, 4 mmol/L), in comparison with CSF/blood glucose ratios (cutoff, 0.4), were associated with higher sensitivity (0.88 vs. 0.77), specificity (0.98 vs. 0.87), and positive (0.96 vs. 0.77) and negative (0.94 vs. 0.87) predictive values. In conclusion, determination of the CSF lactate value is a quick, sensitive, and specific test to identify patients with bacterial meningitis after neurosurgery.

Elderly age is not a negative predictive factor for virological response to therapy with pegylated interferon-α and ribavirin in chronic hepatitis C virus patients

BACKGROUND & AIMS: Age is frequently discussed as negative host factor to achieve a sustained virological response (SVR) to antiviral therapy of chronic hepatitis C. However, elderly patients often show advanced fibrosis/cirrhosis as known negative predictive factor. The aim of this study was to assess age as an independent predictive factor during antiviral therapy. METHODS: Overall, 516 hepatitis C patients were treated with pegylated interferon-α and ribavirin, thereof 66 patients ≥60 years. We analysed the impact of host factors (age, gender, fibrosis, haemoglobin, previous hepatitis C treatment) and viral factors (genotype, viral load) on SVR per therapy course by performing a generalized estimating equations (GEE) regression modelling, a matched pair analysis and a classification tree analysis. RESULTS: Overall, SVR per therapy course was 42.9 and 26.1%, respectively, in young and elderly patients with hepatitis C virus (HCV) genotypes 1/4/6. The corresponding figures for HCV genotypes 2/3 were 74.4 and 84%. In the GEE model, age had no significant influence on achieving SVR. In matched pair analysis, SVR was not different in young and elderly patients (54.2 and 55.9% respectively; P = 0.795 in binominal test). In classification tree analysis, age was not a relevant splitting variable. CONCLUSIONS: Age is not a significant predictive factor for achieving SVR, when relevant confounders are taken into account. As life expectancy in Western Europe at age 60 is more than 20 years, it is reasonable to treat chronic hepatitis C in selected elderly patients with relevant fibrosis or cirrhosis but without major concomitant diseases, as SVR improves survival and reduces carcinogenesis.

Decoding Delay Minimization in Inter-Session Network Coding

Intra-session network coding has been shown to offer significant gains in terms of achievable throughput and delay in settings where one source multicasts data to several clients. In this paper, we consider a more general scenario where multiple sources transmit data to sets of clients over a wireline overlay network. We propose a novel framework for efficient rate allocation in networks where intermediate network nodes have the opportunity to combine packets from different sources using randomized network coding. We formulate the problem as the minimization of the average decoding delay in the client population and solve it with a gradient-based stochastic algorithm. Our optimized inter-session network coding solution is evaluated in different network topologies and is compared with basic intra-session network coding solutions. Our results show the benefits of proper coding decisions and effective rate allocation for lowering the decoding delay when the network is used by concurrent multicast sessions.

Distributed Rate Allocation in Inter-Session Network Coding

In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since this optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity.

Interactive free viewpoint video streaming using prioritized network coding

In free viewpoint applications, the images are captured by an array of cameras that acquire a scene of interest from different perspectives. Any intermediate viewpoint not included in the camera array can be virtually synthesized by the decoder, at a quality that depends on the distance between the virtual view and the camera views available at decoder. Hence, it is beneficial for any user to receive camera views that are close to each other for synthesis. This is however not always feasible in bandwidth-limited overlay networks, where every node may ask for different camera views. In this work, we propose an optimized delivery strategy for free viewpoint streaming over overlay networks. We introduce the concept of layered quality-of-experience (QoE), which describes the level of interactivity offered to clients. Based on these levels of QoE, camera views are organized into layered subsets. These subsets are then delivered to clients through a prioritized network coding streaming scheme, which accommodates for the network and clients heterogeneity and effectively exploit the resources of the overlay network. Simulation results show that, in a scenario with limited bandwidth or channel reliability, the proposed method outperforms baseline network coding approaches, where the different levels of QoE are not taken into account in the delivery strategy optimization.

When small non-coding RNAs meet the ribosome: Tuning the translational machinery

The functions of ribosomes in translation are complex and involve different types of activities critical for decoding the genetic code, linkage of amino acids via amide bonds to form polypeptide chains, as well as the release and proper targeting of the synthesized protein. Non-protein-coding RNAs (ncRNAs) have been recognized to be crucial in establishing regulatory networks.1 However all of the recently discovered ncRNAs involved in translation regulation target the mRNA rather than the ribosome. The main goal of this project is to identify potential novel ncRNAs that directly bind and possibly regulate the ribosome during protein biosynthesis. To address this question we applied various stress conditions to the archaeal model organism Haloferax volcanii and deep-sequenced the ribosome-associated small ncRNA interactome. In total we identified 6.250 ncRNA candidates. Significantly, we observed the emersed presence of tRNA-derived fragments (tRFs). These tRFs have been identified in all domains of life and represent a growing, yet functionally poorly understood, class of ncRNAs. Here we present evidence that tRFs from H. volcanii directly bind to ribosomes. In the presented genomic screen of the ribosome-associated RNome a 26 residue long fragment originating from the 5’ part of valine tRNA was by far the most abundant tRF. The Val-tRF is processed in a stress- dependent manner and was found to primarily target the small ribosomal subunit in vitro and in vivo. As a consequence of ribosome binding, Val-tRF reduces protein synthesis by interfering with peptidyl transferase activity. Therefore this tRF functions as ribosome-bound small ncRNA capable of regulating gene expression in H. volcanii under environmental stress conditions probably by fine-tuning the rate of protein production.2 Currently we are investigating the binding site of this tRF on the 30S subunit in more detail.

Robust meta-analytic-predictive priors in clinical trials with historical control information.

Historical information is always relevant for clinical trial design. Additionally, if incorporated in the analysis of a new trial, historical data allow to reduce the number of subjects. This decreases costs and trial duration, facilitates recruitment, and may be more ethical. Yet, under prior-data conflict, a too optimistic use of historical data may be inappropriate. We address this challenge by deriving a Bayesian meta-analytic-predictive prior from historical data, which is then combined with the new data. This prospective approach is equivalent to a meta-analytic-combined analysis of historical and new data if parameters are exchangeable across trials. The prospective Bayesian version requires a good approximation of the meta-analytic-predictive prior, which is not available analytically. We propose two- or three-component mixtures of standard priors, which allow for good approximations and, for the one-parameter exponential family, straightforward posterior calculations. Moreover, since one of the mixture components is usually vague, mixture priors will often be heavy-tailed and therefore robust. Further robustness and a more rapid reaction to prior-data conflicts can be achieved by adding an extra weakly-informative mixture component. Use of historical prior information is particularly attractive for adaptive trials, as the randomization ratio can then be changed in case of prior-data conflict. Both frequentist operating characteristics and posterior summaries for various data scenarios show that these designs have desirable properties. We illustrate the methodology for a phase II proof-of-concept trial with historical controls from four studies. Robust meta-analytic-predictive priors alleviate prior-data conflicts ' they should encourage better and more frequent use of historical data in clinical trials.

The prevalence and predictive value of dipstick urine protein in HIV-positive persons in Europe.

INTRODUCTION Proteinuria (PTU) is an important marker for the development and progression of renal disease, cardiovascular disease and death, but there is limited information about the prevalence and factors associated with confirmed PTU in predominantly white European HIV+ persons, especially in those with an estimated glomerular filtration rate (eGFR) of 60 mL/min/1.73 m(2). PATIENTS AND METHODS Baseline was defined as the first of two consecutive dipstick urine protein (DPU) measurements during prospective follow-up >1/6/2011 (when systematic data collection began). PTU was defined as two consecutive DUP >1+ (>30 mg/dL) >3 months apart; persons with eGFR <60 at either DPU measurement were excluded. Logistic regression investigated factors associated with PTU. RESULTS A total of 1,640 persons were included, participants were mainly white (n=1,517, 92.5%), male (n=1296, 79.0%) and men having sex with men (n=809; 49.3%). Median age at baseline was 45 (IQR 37-52 years), and CD4 was 570 (IQR 406-760/mm(3)). The median baseline date was 2/12 (IQR 11/11-6/12), and median eGFR was 99 (IQR 88-109 mL/min/1.73 m(2)). Sixty-nine persons had PTU (4.2%, 95% CI 3.2-4.7%). Persons with diabetes had increased odds of PTU, as were those with a prior non-AIDS (1) or AIDS event and those with prior exposure to indinavir. Among females, those with a normal eGFR (>90) and those with prior abacavir use had lower odds of PTU (Figure 1). CONCLUSIONS One in 25 persons with eGFR>60 had confirmed proteinuria at baseline. Factors associated with PTU were similar to those associated with CKD. The lack of association with antiretrovirals, particularly tenofovir, may be due to the cross-sectional design of this study, and additional follow-up is required to address progression to PTU in those without PTU at baseline. It may also suggest other markers are needed to capture the deteriorating renal function associated with antiretrovirals may be needed at higher eGFRs. Our findings suggest PTU is an early marker for impaired renal function.

Prognostic and predictive roles of MGMT protein expression and promoter methylation in sporadic pancreatic neuroendocrine neoplasms.

BACKGROUND/AIMS O(6)-methylguanine-methyltransferase (MGMT) is an important enzyme of DNA repair. MGMT promoter methylation is detectable in a subset of pancreatic neuroendocrine neoplasms (pNEN). A subset of pNEN responds to the alkylating agent temozolomide (TMZ). We wanted to correlate MGMT promoter methylation with MGMT protein loss in pNEN, correlate the findings with clinico-pathological data and determine the role of MGMT to predict response to TMZ chemotherapy. METHODS We analysed a well-characterized collective of 141 resected pNEN with median follow-up of 83 months for MGMT protein expression and promoter methylation using methylation-specific PCR (MSP). A second collective of 10 metastasized, pretreated and progressive patients receiving TMZ was used to examine the predictive role of MGMT by determining protein expression and promoter methylation using primer extension-based quantitative PCR. RESULTS In both collectives there was no correlation between MGMT protein expression and promoter methylation. Loss of MGMT protein was associated with an adverse outcome, this prognostic value, however, was not independent from grade and stage in multivariate analysis. Promoter hypermethylation was significantly associated with response to TMZ. CONCLUSION Loss of MGMT protein expression is associated with adverse outcome in a surgical series of pNET. MGMT promoter methylation could be a predictive marker for TMZ chemotherapy in pNEN, but further, favourably prospective studies will be needed to confirm this result and before this observation can influence clinical routine.