Mouse models of rhinovirus-induced disease and exacerbation of allergic airway inflammation

Rhinoviruses cause serious morbidity and mortality as the major etiological agents of asthma exacerbations and the common cold. A major obstacle to understanding disease pathogenesis and to the development of effective therapies has been the lack of a small-animal model for rhinovirus infection. Of the 100 known rhinovirus serotypes, 90% (the major group) use human intercellular adhesion molecule-1 (ICAM-1) as their cellular receptor and do not bind mouse ICAM-1; the remaining 10% (the minor group) use a member of the low-density lipoprotein receptor family and can bind the mouse counterpart. Here we describe three novel mouse models of rhinovirus infection: minor-group rhinovirus infection of BALB/c mice, major-group rhinovirus infection of transgenic BALB/c mice expressing a mouse-human ICAM-1 chimera and rhinovirus-induced exacerbation of allergic airway inflammation. These models have features similar to those observed in rhinovirus infection in humans, including augmentation of allergic airway inflammation, and will be useful in the development of future therapies for colds and asthma exacerbations

Undergoing Transformation to the Patient Centered Medical Home in Safety Net Health Centers: Perspectives from the Front Lines

Objectives—Safety Net Health Centers (SNHCs), which include Federally Qualified Health Centers (FQHCs) provide primary care for underserved, minority and low income patients. SNHCs across the country are in the process of adopting the Patient Centered Medical Home (PCMH) model, based on promising early implementation data from demonstration projects. However, previous demonstration projects have not focused on the safety net and we know little about PCMH transformation in SNHCs. Design—This qualitative study characterizes early PCMH adoption experiences at SNHCs. Setting and Participants—We interviewed 98 staff,(administrators, providers, and clinical staff) at 20 of 65 SNHCs, from five states, who were participating in the first of a five-year PCMH collaborative, the Safety Net Medical Home Initiative. Main Measures—We conducted 30-45 minute, semi-structured telephone interviews. Interview questions addressed benefits anticipated, obstacles encountered, and lessons learned in transition to PCMH. Results—Anticipated benefits for participating in the PCMH included improved staff satisfaction and patient care and outcomes. Obstacles included staff resistance and lack of financial support for PCMH functions. Lessons learned included involving a range of staff, anticipating resistance, and using data as frequent feedback. Conclusions—SNHCs encounter unique challenges to PCMH implementation, including staff turnover and providing care for patients with complex needs. Staff resistance and turnover may be ameliorated through improved healthcare delivery strategies associated with the PCMH. Creating predictable and continuous funding streams may be more fundamental challenges to PCMH transformation

The Cerebral Microvasculature in Schizophrenia: A Laser Capture Microdissection Study

BACKGROUND: Previous studies of brain and peripheral tissues in schizophrenia patients have indicated impaired energy supply to the brain. A number of studies have also demonstrated dysfunction of the microvasculature in schizophrenia patients. Together these findings are consistent with a hypothesis of blood-brain barrier dysfunction in schizophrenia. In this study, we have investigated the cerebral vascular endothelium of schizophrenia patients at the level of transcriptomics. METHODOLOGY/PRINCIPAL FINDINGS: We used laser capture microdissection to isolate both microvascular endothelial cells and neurons from post mortem brain tissue from schizophrenia patients and healthy controls. RNA was isolated from these cell populations, amplified, and analysed using two independent microarray platforms, Affymetrix HG133plus2.0 GeneChips and CodeLink Whole Human Genome arrays. In the first instance, we used the dataset to compare the neuronal and endothelial data, in order to demonstrate that the predicted differences between cell types could be detected using this methodology. We then compared neuronal and endothelial data separately between schizophrenic subjects and controls. Analysis of the endothelial samples showed differences in gene expression between schizophrenics and controls which were reproducible in a second microarray platform. Functional profiling revealed that these changes were primarily found in genes relating to inflammatory processes. CONCLUSIONS/SIGNIFICANCE: This study provides preliminary evidence of molecular alterations of the cerebral microvasculature in schizophrenia patients, suggestive of a hypo-inflammatory state in this tissue type. Further investigation of the blood-brain barrier in schizophrenia is warranted

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

<p>Abstract</p> <p>Background</p> <p>Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function.</p> <p>Results</p> <p>We experimentally annotated the bacterial pathogen <it>Salmonella </it>Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in <it>Salmonella </it>and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in <it>Salmonella </it>pathogenesis. We also characterized post-translational features in the <it>Salmonella </it>genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our <it>in vivo </it>proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function.</p> <p>Conclusion</p> <p>This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of <it>Salmonella </it>as a resource for systems analysis.</p

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling