sFlt-1 and NTproBNP independently predict mortality in a cohort of heart failure patients.

Objective: Soluble fms-like tyrosine kinase-1 (sFlt-1) is a circulating receptor for VEGF-A. Recent reports of elevated plasma levels of sFlt-1 in coronary heart disease and heart failure (HF) motivated our study aimed at investigating the utility of sFlt-1 as a prognostic biomarker in heart failure patients. Methods: ELISA assays for sFlt-1 and NTproBNP were performed in n=858 patients from a prospective multicentre, observational study (the PEOPLE study) of outcome among patients after appropriate treatment for an episode of acute decompensated HF in New Zealand. Plasma was sampled at a baseline visit and stored at -80°C. Statistical tests were adjusted for patient age at baseline visit, skewed data were log-adjusted and the endpoint for clinical outcome analysis was all-cause death. Patients were followed for a median of 3.63 (range 0.74-5.50) years. Results: Mean baseline plasma sFlt-1 was 125 +/- 2.01 pg/ml. sFlt-1 was higher in patients with HF with reduced ejection fraction (HFrEF) (130 +/- 2.62 pg/ml, n=553) compared to those with HF with preserved EF (HFpEF) (117 +/-3.59 pg/ml, n=305; p=0.005). sFlt-1 correlated with heart rate (r=0.148, p<0.001), systolic blood pressure (r=-0.139, p<0.001) and LVEF (r=-0.088, p=0.019). A Cox proportional hazards model showed sFlt-1 was a predictor of all-cause death (HR=6.30, p<0.001) in the PEOPLE cohort independent of age, NTproBNP, ischaemic aetiology, and NYHA class (n=842, 274 deaths), established predictors of mortality in the PEOPLE cohort. Conclusion: sFlt-1 levels at baseline should be investigated further as a predictor of death; complementary to established prognostic biomarkers in heart failure

Measurement of the B0 anti-B0 oscillation frequency using l- D*+ pairs and lepton flavor tags

The oscillation frequency Delta-md of B0 anti-B0 mixing is measured using the partially reconstructed semileptonic decay anti-B0 -> l- nubar D*+ X. The data sample was collected with the CDF detector at the Fermilab Tevatron collider during 1992 - 1995 by triggering on the existence of two lepton candidates in an event, and corresponds to about 110 pb-1 of pbar p collisions at sqrt(s) = 1.8 TeV. We estimate the proper decay time of the anti-B0 meson from the measured decay length and reconstructed momentum of the l- D*+ system. The charge of the lepton in the final state identifies the flavor of the anti-B0 meson at its decay. The second lepton in the event is used to infer the flavor of the anti-B0 meson at production. We measure the oscillation frequency to be Delta-md = 0.516 +/- 0.099 +0.029 -0.035 ps-1, where the first uncertainty is statistical and the second is systematic.Comment: 30 pages, 7 figures. Submitted to Physical Review

Plasma soluble fms-like tyrosine kinase-1, placental growth factor, and vascular endothelial growth factor system gene variants as predictors of survival in heart failure.

Aims Soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF), components of the vascular endothelial growth factor (VEGF) system, play key roles in angiogenesis. Reports of elevated plasma levels of sFlt-1 and PlGF in coronary heart disease and heart failure (HF) led us to investigate their utility, and VEGF system gene single nucleotide polymorphisms (SNPs), as prognostic biomarkers in HF. Methods and results ELISA assays for sFlt-1, PlGF and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were performed on baseline plasma samples from the PEOPLE cohort (n = 890), a study of outcomes among patients after an episode of acute decompensated HF. Eight SNPs potentially associated with sFlt-1 or PlGF levels were genotyped. sFlt-1 and PlGF were assayed in 201 subjects from the Canterbury Healthy Volunteers Study (CHVS) matched to PEOPLE participants. All-cause death was the major endpoint for clinical outcome considered. In PEOPLE participants, mean plasma levels for both sFlt-1 (125 ± 2.01 pg/ml) and PlGF (17.5 ± 0.21 pg/ml) were higher (both p < 0.044) than in the CHVS cohort (81.2 ± 1.31 pg/ml and 15.5 ± 0.32 pg/ml, respectively). sFlt-1 was higher in HF with reduced ejection fraction compared to HF with preserved ejection fraction (p = 0.005). The PGF gene SNP rs2268616 was univariately associated with death (p = 0.016), and was also associated with PlGF levels, as was rs2268614 genotype. Cox proportional hazards modelling (n = 695, 246 deaths) showed plasma sFlt-1, but not PlGF, predicted survival (hazard ratio 6.44, 95% confidence interval 2.57–16.1; p < 0.001) in PEOPLE, independent of age, NT-proBNP, ischaemic aetiology, diabetic status and beta-blocker therapy. Conclusions Plasma sFlt-1 concentrations have potential as an independent predictor of survival and may be complementary to established prognostic biomarkers in HF

ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties

Difficulties in social communication are part of the phenotypic overlap between autism spectrum disorders (ASD) and schizophrenia. Both conditions follow, however, distinct developmental patterns. Symptoms of ASD typically occur during early childhood, whereas most symptoms characteristic of schizophrenia do not appear before early adulthood. We investigated whether overlap in common genetic in fluences between these clinical conditions and impairments in social communication depends on the developmental stage of the assessed trait. Social communication difficulties were measured in typically-developing youth (Avon Longitudinal Study of Parents and Children,N⩽5553, longitudinal assessments at 8, 11, 14 and 17 years) using the Social Communication Disorder Checklist. Data on clinical ASD (PGC-ASD: 5305 cases, 5305 pseudo-controls; iPSYCH-ASD: 7783 cases, 11 359 controls) and schizophrenia (PGC-SCZ2: 34 241 cases, 45 604 controls, 1235 trios) were either obtained through the Psychiatric Genomics Consortium (PGC) or the Danish iPSYCH project. Overlap in genetic in fluences between ASD and social communication difficulties during development decreased with age, both in the PGC-ASD and the iPSYCH-ASD sample. Genetic overlap between schizophrenia and social communication difficulties, by contrast, persisted across age, as observed within two independent PGC-SCZ2 subsamples, and showed an increase in magnitude for traits assessed during later adolescence. ASD- and schizophrenia-related polygenic effects were unrelated to each other and changes in trait-disorder links reflect the heterogeneity of genetic factors in fluencing social communication difficulties during childhood versus later adolescence. Thus, both clinical ASD and schizophrenia share some genetic in fluences with impairments in social communication, but reveal distinct developmental profiles in their genetic links, consistent with the onset of clinical symptom

Accounting for Population Stratification in Practice: A Comparison of the Main Strategies Dedicated to Genome-Wide Association Studies

Genome-Wide Association Studies are powerful tools to detect genetic variants associated with diseases. Their results have, however, been questioned, in part because of the bias induced by population stratification. This is a consequence of systematic differences in allele frequencies due to the difference in sample ancestries that can lead to both false positive or false negative findings. Many strategies are available to account for stratification but their performances differ, for instance according to the type of population structure, the disease susceptibility locus minor allele frequency, the degree of sampling imbalanced, or the sample size. We focus on the type of population structure and propose a comparison of the most commonly used methods to deal with stratification that are the Genomic Control, Principal Component based methods such as implemented in Eigenstrat, adjusted Regressions and Meta-Analyses strategies. Our assessment of the methods is based on a large simulation study, involving several scenarios corresponding to many types of population structures. We focused on both false positive rate and power to determine which methods perform the best. Our analysis showed that if there is no population structure, none of the tests led to a bias nor decreased the power except for the Meta-Analyses. When the population is stratified, adjusted Logistic Regressions and Eigenstrat are the best solutions to account for stratification even though only the Logistic Regressions are able to constantly maintain correct false positive rates. This study provides more details about these methods. Their advantages and limitations in different stratification scenarios are highlighted in order to propose practical guidelines to account for population stratification in Genome-Wide Association Studies

Discovery of High-Affinity Protein Binding Ligands – Backwards

BACKGROUND: There is a pressing need for high-affinity protein binding ligands for all proteins in the human and other proteomes. Numerous groups are working to develop protein binding ligands but most approaches develop ligands using the same strategy in which a large library of structured ligands is screened against a protein target to identify a high-affinity ligand for the target. While this methodology generates high-affinity ligands for the target, it is generally an iterative process that can be difficult to adapt for the generation of ligands for large numbers of proteins. METHODOLOGY/PRINCIPAL FINDINGS: We have developed a class of peptide-based protein ligands, called synbodies, which allow this process to be run backwards--i.e. make a synbody and then screen it against a library of proteins to discover the target. By screening a synbody against an array of 8,000 human proteins, we can identify which protein in the library binds the synbody with high affinity. We used this method to develop a high-affinity synbody that specifically binds AKT1 with a K(d)<5 nM. It was found that the peptides that compose the synbody bind AKT1 with low micromolar affinity, implying that the affinity and specificity is a product of the bivalent interaction of the synbody with AKT1. We developed a synbody for another protein, ABL1 using the same method. CONCLUSIONS/SIGNIFICANCE: This method delivered a high-affinity ligand for a target protein in a single discovery step. This is in contrast to other techniques that require subsequent rounds of mutational improvement to yield nanomolar ligands. As this technique is easily scalable, we believe that it could be possible to develop ligands to all the proteins in any proteome using this approach

Using system dynamics for collaborative design: a case study

<p>Abstract</p> <p>Background</p> <p>In order to facilitate the collaborative design, system dynamics (SD) with a group modelling approach was used in the early stages of planning a new stroke unit. During six workshops a SD model was created in a multiprofessional group.</p> <p>Aim</p> <p>To explore to which extent and how the use of system dynamics contributed to the collaborative design process.</p> <p>Method</p> <p>A case study was conducted using several data sources.</p> <p>Results</p> <p>SD supported a collaborative design, by facilitating an explicit description of stroke care process, a dialogue and a joint understanding. The construction of the model obliged the group to conceptualise the stroke care and experimentation with the model gave the opportunity to reflect on care.</p> <p>Conclusion</p> <p>SD facilitated the collaborative design process and should be integrated in the early stages of the design process as a quality improvement tool.</p

Efficiency of Ontario primary care physicians across payment models : a stochastic frontier analysis

Objective The study examines the relationship between the primary care model that a physician belongs to and the efficiency of the primary care physician in Ontario, Canada. Methods Survey data were collected from 183 self-selected physicians and linked to administrative databases to capture the provision of services to the patients served for the 12 month period ending June 30, 2013, and the characteristics of the patients at the beginning of the study period. Two stochastic frontier regression models were used to estimate efficiency scores and parameters for two separate outputs: the number of distinct patients seen and the number of visits. Results Because of missing data, only 165 physicians were included in the analyses. The average efficiency was 0.72 for both outputs with scores varying from 4 % to 93 % for the visits and 5 % to 94 % for the number of patients seen. We observed that there were both very low and very high efficiency scores within each model. These variations were larger than variations in average scores across models

Thermodynamic Additivity of Sequence Variations: An Algorithm for Creating High Affinity Peptides Without Large Libraries or Structural Information

BACKGROUND: There is a significant need for affinity reagents with high target affinity/specificity that can be developed rapidly and inexpensively. Existing affinity reagent development approaches, including protein mutagenesis, directed evolution, and fragment-based design utilize large libraries and/or require structural information thereby adding time and expense. Until now, no systematic approach to affinity reagent development existed that could produce nanomolar affinity from small chemically synthesized peptide libraries without the aid of structural information. METHODOLOGY/PRINCIPAL FINDINGS: Based on the principle of additivity, we have developed an algorithm for generating high affinity peptide ligands. In this algorithm, point-variations in a lead sequence are screened and combined in a systematic manner to achieve additive binding energies. To demonstrate this approach, low-affinity lead peptides for multiple protein targets were identified from sparse random sequence space and optimized to high affinity in just two chemical steps. In one example, a TNF-α binding peptide with K(d) = 90 nM and high target specificity was generated. The changes in binding energy associated with each variation were generally additive upon combining variations, validating the basis of the algorithm. Interestingly, cooperativity between point-variations was not observed, and in a few specific cases, combinations were less than energetically additive. CONCLUSIONS/SIGNIFICANCE: By using this additivity algorithm, peptide ligands with high affinity for protein targets were generated. With this algorithm, one of the highest affinity TNF-α binding peptides reported to date was produced. Most importantly, high affinity was achieved from small, chemically-synthesized libraries without the need for structural information at any time during the process. This is significantly different than protein mutagenesis, directed evolution, or fragment-based design approaches, which rely on large libraries and/or structural guidance. With this algorithm, high affinity/specificity peptide ligands can be developed rapidly, inexpensively, and in an entirely chemical manner