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ObjectiveThis report aims to determine the safety, pharmacokinetics (PK) and efficacy of subcutaneous golimumab in active polyarticular-course juvenile idiopathic arthritis (polyJIA).MethodsIn this three-part randomised double-blinded placebo-controlled withdrawal trial, all patients received open-label golimumab (30 mg/m2 of body surface area; maximum: 50 mg/dose) every 4 weeks together with weekly methotrexate during Part 1 (weeks 0–16). Patients with at least 30% improvement per American College of Rheumatology Criteria for JIA (JIA ACR30) in Part 1 entered the double-blinded Part 2 (weeks 16–48) after 1:1 randomisation to continue golimumab or start placebo. In Part 3, golimumab was continued or could be restarted as in Part 1. The primary outcome was JIA flares in Part 2; secondary outcomes included JIA ACR50/70/90 responses, clinical remission, PK and safety.ResultsAmong 173 patients with polyJIA enrolled, 89.0% (154/173) had a JIA ACR30 response and 79.2%/65.9%/36.4% demonstrated JIA ACR50/70/90 responses in Part 1. At week 48, the primary endpoint was not met as treatment groups had comparable JIA flare rates (golimumab vs placebo: 32/78=41% vs 36/76=47%; p=0.41), and rates of clinical remission were comparable (golimumab vs placebo: 10/78=12.8% vs 9/76=11.8%). Adverse event and serious adverse event rates were similar in the treatment groups during Part 2. Injection site reactions occurred with <1% of all injections. PK analysis confirmed adequate golimumab dosing for polyJIA.ConclusionAlthough the primary endpoint was not met, golimumab resulted in rapid, clinically meaningful, improvement in children with active polyJIA. Golimumab was well tolerated, and no unexpected safety events occurred.Clinical Trial RegistrationNCT01230827; Results.

Background Although genome-wide association studies (GWAS) have identified over 100 genetic loci associated with rheumatoid arthritis (RA), our ability to translate these results into disease understanding and novel therapeutics is limited. Most RA GWAS loci reside outside of protein-coding regions and likely affect distal transcriptional enhancers. Furthermore, GWAS do not identify the cell types where the associated causal gene functions. Thus, mapping the transcriptional regulatory roles of GWAS hits and the relevant cell types will lead to better understanding of RA pathogenesis. Results We combine the whole-genome sequences and blood transcription profiles of 377 RA patients and identify over 6000 unique genes with expression quantitative trait loci (eQTLs). We demonstrate the quality of the identified eQTLs through comparison to non-RA individuals. We integrate the eQTLs with immune cell epigenome maps, RA GWAS risk loci, and adjustment for linkage disequilibrium to propose target genes of immune cell enhancers that overlap RA risk loci. We examine 20 immune cell epigenomes and perform a focused analysis on primary monocytes, B cells, and T cells. Conclusions We highlight cell-specific gene associations with relevance to RA pathogenesis including the identification of FCGR2B in B cells as possessing both intragenic and enhancer regulatory GWAS hits. We show that our RA patient cohort derived eQTL network is more informative for studying RA than that from a healthy cohort. While not experimentally validated here, the reported eQTLs and cell type-specific RA risk associations can prioritize future experiments with the goal of elucidating the regulatory mechanisms behind genetic risk associations.

Background The tumor necrosis factor (TNF) superfamily cytokine TNF-like protein 1A (TL1A) and its receptor DR3 are essential for diverse animal models of autoimmune disease and may be pathogenic in rheumatoid arthritis (RA). However, the relationship of TL1A to disease duration, activity, and response to anti-TNF and other therapies in RA is not clear. Methods We measured soluble TL1A in synovial fluid (SF), serum, or plasma from RA first-degree relatives (FDRs) and in early RA and established disease. We measured the effects of anti-TNF and methotrexate (MTX) therapy on circulating TL1A from multiple independent RA treatment trials. We also determined the ability of a blocking anti-TL1A antibody to inhibit clinical disease and articular bone destruction in the murine collagen-induced arthritis (CIA) model of human RA. Results Soluble TL1A was specifically elevated in the blood and SF of patients with RA compared to patients with other diseases and was elevated early in disease and in at-risk anti-cyclic citrullinated peptide (CCP) (+) first-degree relatives (FDRs). Therapeutic TNF inhibition reduced serum TL1A in both responders and non-responders, whereas TL1A declined following MTX treatment only in responders. In murine CIA, TL1A blockade was clinically efficacious and reduced bone erosions. Conclusions TL1A is specifically elevated in RA from early in the disease course and in at-risk FDRs. The decline in TL1A after TNF blockade suggests that TL1A levels may be a useful biomarker for TNF activity in RA. These results support the further investigation of the relationship between TL1A and TNF and TL1A blockade as a potential therapeutic strategy in RA.

Motivation Next-generation sequencing (NGS) technologies have become much more efficient, allowing whole human genomes to be sequenced faster and cheaper than ever before. However, processing the raw sequence reads associated with NGS technologies requires care and sophistication in order to draw compelling inferences about phenotypic consequences of variation in human genomes. It has been shown that different approaches to variant calling from NGS data can lead to different conclusions. Ensuring appropriate accuracy and quality in variant calling can come at a computational cost. Results We describe our experience implementing and evaluating a group-based approach to calling variants on large numbers of whole human genomes. We explore the influence of many factors that may impact the accuracy and efficiency of group-based variant calling, including group size, the biogeographical backgrounds of the individuals who have been sequenced, and the computing environment used. We make efficient use of the Gordon supercomputer cluster at the San Diego Supercomputer Center by incorporating job-packing and parallelization considerations into our workflow while calling variants on 437 whole human genomes generated as part of large association study. Conclusions We ultimately find that our workflow resulted in high-quality variant calls in a computationally efficient manner. We argue that studies like ours should motivate further investigations combining hardware-oriented advances in computing systems with algorithmic developments to tackle emerging ‘big data’ problems in biomedical research brought on by the expansion of NGS technologies.

Gut microbes shape many aspects of organismal biology, yet how these key bacteria transmit among hosts in natural populations remains poorly understood. Recent work in mammals has emphasized either transmission through social contacts or indirect transmission through environmental contact, but the relative importance of different routes has not been directly assessed. Here we used a novel radio-frequency identification-based tracking system to collect long-term high-resolution data on social relationships, space use and microhabitat in a wild population of mice ( Apodemus sylvaticus ), while regularly characterizing their gut microbiota with 16S ribosomal RNA profiling. Through probabilistic modelling of the resulting data, we identify positive and statistically distinct signals of social and environmental transmission, captured by social networks and overlap in home ranges, respectively. Strikingly, microorganisms with distinct biological attributes drove these different transmission signals. While the social network effect on microbiota was driven by anaerobic bacteria, the effect of shared space was most influenced by aerotolerant spore-forming bacteria. These findings support the prediction that social contact is important for the transfer of microorganisms with low oxygen tolerance, while those that can tolerate oxygen or form spores may be able to transmit indirectly through the environment. Overall, these results suggest social and environmental transmission routes can spread biologically distinct members of the mammalian gut microbiota. Long-term high-resolution data on social relationships, space use and microhabitat in a wild population of mice ( Apodemus sylvaticus ), accompanied by sampling of the gut microbiota, show that distinct sets of microorganisms dominate social and environmental transmission routes of microbiota. Microorganisms with low oxygen tolerance are more reliant on social transmission.

Over the past three decades, marine resource management has shifted conceptually from top-down sectoral approaches towards the more systems-oriented multi-stakeholder frameworks of integrated coastal management and ecosystem-based conservation. However, the successful implementation of such frameworks is commonly hindered by a lack of cross-disciplinary knowledge transfer, especially between natural and social sciences. This review represents a holistic synthesis of three decades of change in the oceanography, biology and human dimension of False Bay, South Africa. The productivity of marine life in this bay and its close vicinity to the steadily growing metropolis of Cape Town have led to its socio-economic significance throughout history. Considerable research has highlighted shifts driven by climate change, human population growth, serial overfishing, and coastal development. Upwelling-inducing winds have increased in the region, leading to cooling and likely to nutrient enrichment of the bay. Subsequently the distributions of key components of the marine ecosystem have shifted eastward, including kelp, rock lobsters, seabirds, pelagic fish, and several alien invasive species. Increasing sea level and exposure to storm surges contribute to coastal erosion of the sandy shorelines in the bay, causing losses in coastal infrastructure and posing risk to coastal developments. Since the 1980s, the human population of Cape Town has doubled, and with it pollution has amplified. Overfishing has led to drastic declines in the catches of numerous commercially and recreationally targeted fish, and illegal fishing is widespread. The tourism value of the bay contributes substantially to the country’s economy, and whale watching, shark-cage diving and water sports have become important sources of revenue. Compliance with fisheries and environmental regulations would benefit from a systems-oriented approach whereby coastal systems are managed holistically, embracing both social and ecological goals. In this context, we synthesize knowledge and provide recommendations for multidisciplinary research and monitoring to achieve a better balance between developmental and environmental agendas.

Gut microbes shape many aspects of organismal biology, yet how these key bacteria transmit among hosts in natural populations remains poorly understood. Recent work in mammals has emphasized either transmission through social contacts or indirect transmission through environmental contact, but the relative importance of different routes has not been directly assessed. Here, we used a novel RFID-based tracking system to collect long-term high resolution data on social relationships, space use and microhabitat in a wild population of mice (Apodemus sylvaticus), while regularly characterising their gut microbiota. Through probabilistic modelling of the resulting data, we identify positive and statistically distinct signals of social and environmental transmission, captured by social networks and overlap in home ranges respectively. Strikingly, microbes with distinct biological attributes drove these different transmission signals. While aerotolerant spore-forming bacteria drove the effect of shared space use, a mix of taxa but especially anaerobic bacteria underpinned the social network’s effect on gut microbiota similarity. These findings provide the first evidence for parallel social and environmental transmission of gut microbes that involve biologically distinct subsets of the mammalian gut microbiota. Aura Raulo designed the study, helped develop the new RFID tracking technology, collected the data from Wytham, completed all laboratory analyses on gut microbiota profiling prior to sequencing, developed analytical methods, analysed the data and wrote the manuscript Paul Bürkner helped design the Bayesian probabilistic modeling framework and provided feedback on the manuscript Jarrah Dale helped collect field data using RFID loggers Holly English helped collect field data using RFID loggers and provided feedback on home range analyses Genevieve Finerty helped with home range analysis and the analysis of microhabitat variation and provided feedback on the manuscript Curt Lamberth led development of RFID tracking devices and helped collect field data from Wytham Josh Firth supervised the research project, developed social network analysis methods and provided feedback on the analyses and the manuscript Tim Coulson supervised the research project and provided feedback on the analyses and the manuscript Sarah Knowles supervised the research project, helped develop the tracking technology and design the study, collected data from Wytham, planned and supervised laboratory methods, developed analytical methods and provided feedback on analyses and the manuscript.