Essential role for proteinase-activated receptor-2 in arthritis

Using physiological, pharmacological, and gene disruption approaches, we demonstrate that proteinase-activated receptor-2 (PAR-2) plays a pivotal role in mediating chronic inflammation. Using an adjuvant monoarthritis model of chronic inflammation, joint swelling was substantially inhibited in PAR-2-deficient mice, being reduced by more than fourfold compared with wild-type mice, with virtually no histological evidence of joint damage. Mice heterozygous for PAR-2 gene disruption showed an intermediate phenotype. PAR-2 expression, normally limited to endothelial cells in small arterioles, was substantially upregulated 2 weeks after induction of inflammation, both in synovium and in other periarticular tissues. PAR-2 agonists showed potent proinflammatory effects as intra-articular injection of ASKH95, a novel synthetic PAR-2 agonist, induced prolonged joint swelling and synovial hyperemia. Given the absence of the chronic inflammatory response in the PAR-2-deficient mice, our findings demonstrate a key role for PAR-2 in mediating chronic inflammation, thereby identifying a novel and important therapeutic target for the management of chronic inflammatory diseases such as rheumatoid arthritis

Proteinase-activated receptor 2 modulates OA-related pain, cartilage and bone pathology

Objective Proteinase-activated receptor 2 (PAR2) deficiency protects against cartilage degradation in experimental osteoarthritis (OA). The wider impact of this pathway upon OA-associated pathologies such as osteophyte formation and pain is unknown. Herein, we investigated early temporal bone and cartilage changes in experimental OA in order to further elucidate the role of PAR2 in OA pathogenesis. Methods OA was induced in wild-type (WT) and PAR2-deficient (PAR2−/−) mice by destabilisation of the medial meniscus (DMM). Inflammation, cartilage degradation and bone changes were monitored using histology and microCT. In gene rescue experiments, PAR2−/− mice were intra-articularly injected with human PAR2 (hPAR2)-expressing adenovirus. Dynamic weight bearing was used as a surrogate of OA-related pain. Results Osteophytes formed within 7 days post-DMM in WT mice but osteosclerosis was only evident from 14 days post induction. Importantly, PAR2 was expressed in the proliferative/hypertrophic chondrocytes present within osteophytes. In PAR2−/− mice, osteophytes developed significantly less frequently but, when present, were smaller and of greater density; no osteosclerosis was observed in these mice up to day 28. The pattern of weight bearing was altered in PAR2−/− mice, suggesting reduced pain perception. The expression of hPAR2 in PAR2−/− mice recapitulated osteophyte formation and cartilage damage similar to that observed in WT mice. However, osteosclerosis was absent, consistent with lack of hPAR2 expression in subchondral bone. Conclusions This study clearly demonstrates PAR2 plays a critical role, via chondrocytes, in osteophyte development and subchondral bone changes, which occur prior to PAR2-mediated cartilage damage. The latter likely occurs independently of OA-related bone changes

SAMQA: error classification and validation of high-throughput sequenced read data

<p>Abstract</p> <p>Background</p> <p>The advances in high-throughput sequencing technologies and growth in data sizes has highlighted the need for scalable tools to perform quality assurance testing. These tests are necessary to ensure that data is of a minimum necessary standard for use in downstream analysis. In this paper we present the SAMQA tool to rapidly and robustly identify errors in population-scale sequence data.</p> <p>Results</p> <p>SAMQA has been used on samples from three separate sets of cancer genome data from The Cancer Genome Atlas (TCGA) project. Using technical standards provided by the SAM specification and biological standards defined by researchers, we have classified errors in these sequence data sets relative to individual reads within a sample. Due to an observed linearithmic speedup through the use of a high-performance computing (HPC) framework for the majority of tasks, poor quality data was identified prior to secondary analysis in significantly less time on the HPC framework than the same data run using alternative parallelization strategies on a single server.</p> <p>Conclusions</p> <p>The SAMQA toolset validates a minimum set of data quality standards across whole-genome and exome sequences. It is tuned to run on a high-performance computational framework, enabling QA across hundreds gigabytes of samples regardless of coverage or sample type.</p

The tyranny of the male preserve

Within this paper I draw on short vignettes and quotes taken from a two-year ethnographic study of boxing to think through the continuing academic merit of the notion of the male preserve. This is an important task due to evidence of shifts in social patterns of gender that have developed since the idea was first proposed in the 1970s. In aligning theoretical contributions from Lefebvre and Butler to discussions of the male preserve, we are able to add nuance to our understanding of how such social spaces are engrained with and produced by the lingering grasp of patriarchal narratives. In particular, by situating the male preserve within shifting social processes, whereby certain men’s power is increasingly undermined, I highlight the production of space within which narratives connecting men to violence, aggression and physical power can be consumed, performed and reified in a relatively unrestricted form. This specific case study contributes to gender theory as an illustration of a way in which we might explore and understand social enclaves where certain people are able to lay claim to space and power. As such, I argue that the notion of the male preserve is still a useful conceptual, theoretical and political device especially when considered as produced by the tyranny of gender power through the dramatic representation and reification of behaviours symbolically linked to patriarchal narrations of manhood

The scale of population structure in Arabidopsis thaliana

The population structure of an organism reflects its evolutionary history and influences its evolutionary trajectory. It constrains the combination of genetic diversity and reveals patterns of past gene flow. Understanding it is a prerequisite for detecting genomic regions under selection, predicting the effect of population disturbances, or modeling gene flow. This paper examines the detailed global population structure of Arabidopsis thaliana. Using a set of 5,707 plants collected from around the globe and genotyped at 149 SNPs, we show that while A. thaliana as a species self-fertilizes 97% of the time, there is considerable variation among local groups. This level of outcrossing greatly limits observed heterozygosity but is sufficient to generate considerable local haplotypic diversity. We also find that in its native Eurasian range A. thaliana exhibits continuous isolation by distance at every geographic scale without natural breaks corresponding to classical notions of populations. By contrast, in North America, where it exists as an exotic species, A. thaliana exhibits little or no population structure at a continental scale but local isolation by distance that extends hundreds of km. This suggests a pattern for the development of isolation by distance that can establish itself shortly after an organism fills a new habitat range. It also raises questions about the general applicability of many standard population genetics models. Any model based on discrete clusters of interchangeable individuals will be an uneasy fit to organisms like A. thaliana which exhibit continuous isolation by distance on many scales

Evidence of a Causal Association Between Insulinemia and Endometrial Cancer: A Mendelian Randomization Analysis.

BACKGROUND: Insulinemia and type 2 diabetes (T2D) have been associated with endometrial cancer risk in numerous observational studies. However, the causality of these associations is uncertain. Here we use a Mendelian randomization (MR) approach to assess whether insulinemia and T2D are causally associated with endometrial cancer. METHODS: We used single nucleotide polymorphisms (SNPs) associated with T2D (49 variants), fasting glucose (36 variants), fasting insulin (18 variants), early insulin secretion (17 variants), and body mass index (BMI) (32 variants) as instrumental variables in MR analyses. We calculated MR estimates for each risk factor with endometrial cancer using an inverse-variance weighted method with SNP-endometrial cancer associations from 1287 case patients and 8273 control participants. RESULTS: Genetically predicted higher fasting insulin levels were associated with greater risk of endometrial cancer (odds ratio [OR] per standard deviation = 2.34, 95% confidence internal [CI] = 1.06 to 5.14, P = .03). Consistently, genetically predicted higher 30-minute postchallenge insulin levels were also associated with endometrial cancer risk (OR = 1.40, 95% CI = 1.12 to 1.76, P = .003). We observed no associations between genetic risk of type 2 diabetes (OR = 0.91, 95% CI = 0.79 to 1.04, P = .16) or higher fasting glucose (OR = 1.00, 95% CI = 0.67 to 1.50, P = .99) and endometrial cancer. In contrast, endometrial cancer risk was higher in individuals with genetically predicted higher BMI (OR = 3.86, 95% CI = 2.24 to 6.64, P = 1.2x10(-6)). CONCLUSION: This study provides evidence to support a causal association of higher insulin levels, independently of BMI, with endometrial cancer risk.This study was supported by MRC grant MC_UU_12015/1 and by the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement n° 115372 (contributions from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies). ANECS recruitment was supported by project grants from the National Health and Medical Research Council of Australia (ID#339435), The Cancer Council Queensland (ID#4196615) and Cancer Council Tasmania (ID#403031 and ID#457636). SEARCH recruitment was funded by a programme grant from Cancer Research UK [C490/A10124]. Case genotyping was supported by the National Health and Medical Research Council (ID#552402). Control data was generated by the Wellcome Trust Case Control Consortium (WTCCC), and a full list of the investigators who contributed to the generation of the data is available from the WTCCC website. We acknowledge use of DNA from the British 1958 Birth Cohort collection, funded by the Medical Research Council grant G0000934 and the Wellcome Trust grant 068545/Z/02. Funding for this project was provided by the Wellcome Trust under award 085475. Recruitment of the QIMR controls was supported by the National Health and Medical Research Council of Australia (NHMRC). The University of Newcastle, the Gladys M Brawn Senior Research Fellowship scheme, The Vincent Fairfax Family Foundation, the Hunter Medical Research Institute and the Hunter Area Pathology Service all contributed towards the costs of establishing the Hunter Community Study. K.T.N. was supported by the Gates Cambridge Trust. R.K.S. is supported by the Wellcome Trust (grant number WT098498). A.B.S. is supported by the National Health and Medical Research Council (NHMRC) Fellowship Scheme. D.F.E. is a Principal Research Fellow of Cancer Research UK. A.M.D is supported by the Joseph Mitchell Trust.This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/jnci/djv17

A genome-wide association study identifies protein quantitative trait loci (pQTLs)

There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10 -57), CCL4L1 (p = 3.9×10-21), IL18 (p = 6.8×10-13), LPA (p = 4.4×10-10), GGT1 (p = 1.5×10-7), SHBG (p = 3.1×10-7), CRP (p = 6.4×10-6) and IL1RN (p = 7.3×10-6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10-40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways. © 2008 Melzer et al

A Common Variant at the 14q32 Endometrial Cancer Risk Locus Activates AKT1 through YY1 Binding.

A recent meta-analysis of multiple genome-wide association and follow-up endometrial cancer case-control datasets identified a novel genetic risk locus for this disease at chromosome 14q32.33. To prioritize the functional SNP(s) and target gene(s) at this locus, we employed an in silico fine-mapping approach using genotyped and imputed SNP data for 6,608 endometrial cancer cases and 37,925 controls of European ancestry. Association and functional analyses provide evidence that the best candidate causal SNP is rs2494737. Multiple experimental analyses show that SNP rs2494737 maps to a silencer element located within AKT1, a member of the PI3K/AKT/MTOR intracellular signaling pathway activated in endometrial tumors. The rs2494737 risk A allele creates a YY1 transcription factor-binding site and abrogates the silencer activity in luciferase assays, an effect mimicked by transfection of YY1 siRNA. Our findings suggest YY1 is a positive regulator of AKT1, mediating the stimulatory effects of rs2494737 increasing endometrial cancer risk. Identification of an endometrial cancer risk allele within a member of the PI3K/AKT signaling pathway, more commonly activated in tumors by somatic alterations, raises the possibility that well tolerated inhibitors targeting this pathway could be candidates for evaluation as chemopreventive agents in individuals at high risk of developing endometrial cancer.The QIMR Berghofer groups were supported by a Rio Tinto Ride to Conquer Cancer (RTCC)/Weekend to End Women's Cancers (WEWC) Grant and NHMRC project grants 1058415 to SLE and 1031333 to ABS. ABS is supported by an NHMRC Senior Research Fellowship (1061779). DFE is a Principal Research Fellow of CR-UK.This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by Cell Press