Tissue factor and factor VIIa – Hemostasis and beyond

Initiation of the coagulation cascade via exposure of active tissue factor (TF) to blood and formation of the factor VIIa/TF complex is essential for hemostasis and is an initial procoagulant signal in thrombosis. As of early 2012, over 20,000 articles listed on PubMed describe advances in the understanding of TF biology in the settings of hemostasis and thrombosis, as well as in signaling events in cancer, sickle cell anemia, hyperlipidemia, and a broad spectrum of inflammatory disorders. It is both inspiring and humbling, then, to consider not only what has been learned about TF regulation, but also the number of questions still remaining about its role in physiology. This supplement reviews both well-accepted and currently-controversial topics in coagulation and factor VIIa/TF biology, with particular foci on non-hemostatic roles of TF, innovative approaches for the treatment of hemophilia, and novel in vivo models of bleeding and thrombosis

TFPIα Interacts with FVa and FXa to Inhibit Prothrombinase During the Initiation of Coagulation

Tissue factor pathway inhibitor α (TFPIα) inhibits prothrombinase, the thrombin-generating complex of factor Xa (FXa) and factor Va (FVa), during the initiation of coagulation. This inhibition requires binding of a conserved basic region within TFPIα to a conserved acidic region in FXa-activated and platelet-released FVa. In this study, the contribution of interactions between TFPIα and the FXa active site and FVa heavy chain to prothrombinase inhibition were examined to further define the inhibitory biochemistry. Removal of FXa active site binding by mutation or by deletion of the second Kunitz domain (K2) of TFPIα produced 17- or 34-fold weaker prothrombinase inhibition, respectively, establishing that K2 binding to the FXa active site is required for efficient inhibition. Substitution of the TFPIα basic region uncharged residues (Leu252, Ile253, Thr255) with Ala (TFPI-AAKA) produced 5.8-fold decreased inhibition. This finding was confirmed using a basic region peptide (Leu252-Lys261) and Ala substitution peptides, which established that the uncharged residues are required for prothrombinase inhibitory activity but not for binding the FVa acidic region. This suggests that the uncharged residues mediate a secondary interaction with FVa subsequent to acidic region binding. This secondary interaction seems to be with the FVa heavy chain, because the FV Leiden mutation weakened prothrombinase inhibition by TFPIα but did not alter TFPI-AAKA inhibitory activity. Thus, efficient inhibition of prothrombinase by TFPIα requires at least 3 intermolecular interactions: (1) the TFPIα basic region binds the FVa acidic region, (2) K2 binds the FXa active site, and (3) Leu252-Thr255 binds the FVa heavy chain

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Patient Uncertainty Questionnaire-Rheumatology (PUQ-R): development and validation of a new patient-reported outcome instrument for systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) in a mixed methods study

Background An in-depth qualitative exploration of uncertainty in systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) led to the development of a five-domain conceptual framework of patient uncertainty in these two conditions. The purpose of this study was to develop and evaluate a new patient-reported outcome (PRO) instrument for patient uncertainty in SLE and RA on the basis of this empirically developed conceptual framework. Methods Cognitive debriefing interviews were conducted to pre-test the initial items generated on the basis of the preliminary qualitative exploration of patient uncertainty in SLE and RA. Two separate field tests were conducted in five hospital sites to evaluate the measurement properties of the new instrument; the first to identify and form scales, and the second to assess measurement properties of the final version in an independent sample. Psychometric evaluation was conducted in line with the Rasch Measurement Theory (RMT), examining the extent to which sample to scale targeting was satisfactory, measurement scales were constructed effectively and the sample was measured successfully. Traditional psychometric techniques were also used to provide complementary analyses best understood by clinicians. Results Pre-testing supported the relevance, acceptability and comprehensibility of the initial items. Findings indicated that the Patient Uncertainty Questionnaire for Rheumatology PUQ-R instrument fulfilled the expectations of RMT to a large extent (including person separation index 0.73 – 0.91). The PUQ-R comprises 49 items across five scales; symptoms and flares (14 items), medication (11 items), trust in doctor (8 items), self-management (6 items) and impact (10 items) which further displayed excellent measurement properties as assessed against the traditional psychometric criteria (including Cronbach’s alpha 0.82 – 0.93). Conclusion The PUQ-R has been developed and evaluated specifically for patients with SLE and RA. By quantifying uncertainty, the PUQ-R has the potential to support evidence-based management programmes and research

Safety and Immunogenicity of a Recombinant Plasmodium falciparum AMA1 Malaria Vaccine Adjuvanted with Alhydrogel™, Montanide ISA 720 or AS02

Contains fulltext : 71100.pdf (publisher's version ) (Open Access)BACKGROUND: Plasmodium falciparum Apical Membrane Antigen 1 (PfAMA1) is a candidate vaccine antigen expressed by merozoites and sporozoites. It plays a key role in red blood cell and hepatocyte invasion that can be blocked by antibodies. METHODOLOGY/PRINCIPAL FINDINGS: We assessed the safety and immunogenicity of recombinant PfAMA1 in a dose-escalating, phase Ia trial. PfAMA1 FVO strain, produced in Pichia pastoris, was reconstituted at 10 microg and 50 microg doses with three different adjuvants, Alhydrogel, Montanide ISA720 and AS02 Adjuvant System. Six randomised groups of healthy male volunteers, 8-10 volunteers each, were scheduled to receive three immunisations at 4-week intervals. Safety and immunogenicity data were collected over one year. Transient pain was the predominant injection site reaction (80-100%). Induration occurred in the Montanide 50 microg group, resulting in a sterile abscess in two volunteers. Systemic adverse events occurred mainly in the AS02 groups lasting for 1-2 days. Erythema was observed in 22% of Montanide and 59% of AS02 group volunteers. After the second dose, six volunteers in the AS02 group and one in the Montanide group who reported grade 3 erythema (>50 mm) were withdrawn as they met the stopping criteria. All adverse events resolved. There were no vaccine-related serious adverse events. Humoral responses were highest in the AS02 groups. Antibodies showed activity in an in vitro growth inhibition assay up to 80%. Upon stimulation with the vaccine, peripheral mononuclear cells from all groups proliferated and secreted IFNgamma and IL-5 cytokines. CONCLUSIONS/SIGNIFICANCE: All formulations showed distinct reactogenicity profiles. All formulations with PfAMA1 were immunogenic and induced functional antibodies. TRIAL REGISTRATION: (Clinicaltrials.gov) NCT00730782

Large genome-wide association study identifies three novel risk variants for restless legs syndrome

Funder: Scottish Government; doi: https://doi.org/10.13039/100012095Funder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289Abstract: Restless legs syndrome (RLS) is a common neurological sensorimotor disorder often described as an unpleasant sensation associated with an urge to move the legs. Here we report findings from a meta-analysis of genome-wide association studies of RLS including 480,982 Caucasians (cases = 10,257) and a follow up sample of 24,977 (cases = 6,651). We confirm 19 of the 20 previously reported RLS sequence variants at 19 loci and report three novel RLS associations; rs112716420-G (OR = 1.25, P = 1.5 × 10−18), rs10068599-T (OR = 1.09, P = 6.9 × 10−10) and rs10769894-A (OR = 0.90, P = 9.4 × 10−14). At four of the 22 RLS loci, cis-eQTL analysis indicates a causal impact on gene expression. Through polygenic risk score for RLS we extended prior epidemiological findings implicating obesity, smoking and high alcohol intake as risk factors for RLS. To improve our understanding, with the purpose of seeking better treatments, more genetics studies yielding deeper insights into the disease biology are needed

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility