VectorBase: a home for invertebrate vectors of human pathogens

VectorBase () is a web-accessible data repository for information about invertebrate vectors of human pathogens. VectorBase annotates and maintains vector genomes providing an integrated resource for the research community. Currently, VectorBase contains genome information for two organisms: Anopheles gambiae, a vector for the Plasmodium protozoan agent causing malaria, and Aedes aegypti, a vector for the flaviviral agents causing Yellow fever and Dengue fever

Beta Dips in the Gaia Era: Simulation Predictions of the Galactic Velocity Anisotropy Parameter (β) for Stellar Halos

The velocity anisotropy parameter, β, is a measure of the kinematic state of orbits in the stellar halo, which holds promise for constraining the merger history of the Milky Way (MW). We determine global trends for β as a function of radius from three suites of simulations, including accretion-only and cosmological hydrodynamic simulations. We find that the two types of simulations are consistent and predict strong radial anisotropy ($\langle \beta \rangle \sim 0.7$) for Galactocentric radii greater than 10 kpc. Previous observations of β for the MW's stellar halo claim a detection of an isotropic or tangential "dip" at r ~ 20 kpc. Using the N-body+SPH simulations, we investigate the temporal persistence, population origin, and severity of "dips" in β. We find that dips in the in situ stellar halo are long-lived, while dips in the accreted stellar halo are short-lived and tied to the recent accretion of satellite material. We also find that a major merger as early as z ~ 1 can result in a present-day low (isotropic to tangential) value of β over a broad range of radii and angles. While all of these mechanisms are plausible drivers for the β dip observed in the MW, each mechanism in the simulations has a unique metallicity signature associated with it, implying that future spectroscopic surveys could distinguish between them. Since an accurate knowledge of β(r) is required for measuring the mass of the MW halo, we note that significant transient dips in β could cause an overestimate of the halo's mass when using spherical Jeans equation modeling

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group

The prostaglandin D2 receptor 2 pathway in asthma: a key player in airway inflammation

Abstract Asthma is characterised by chronic airway inflammation, airway obstruction and hyper-responsiveness. The inflammatory cascade in asthma comprises a complex interplay of genetic factors, the airway epithelium, and dysregulation of the immune response. Prostaglandin D2 (PGD2) is a lipid mediator, predominantly released from mast cells, but also by other immune cells such as TH2 cells and dendritic cells, which plays a significant role in the pathophysiology of asthma. PGD2 mainly exerts its biological functions via two G-protein-coupled receptors, the PGD2 receptor 1 (DP1) and 2 (DP2). The DP2 receptor is mainly expressed by the key cells involved in type 2 immune responses, including TH2 cells, type 2 innate lymphoid cells and eosinophils. The DP2 receptor pathway is a novel and important therapeutic target for asthma, because increased PGD2 production induces significant inflammatory cell chemotaxis and degranulation via its interaction with the DP2 receptor. This interaction has serious consequences in the pulmonary milieu, including the release of pro-inflammatory cytokines and harmful cationic proteases, leading to tissue remodelling, mucus production, structural damage, and compromised lung function. This review will discuss the importance of the DP2 receptor pathway and the current understanding of its role in asthma