Predictors and outcomes of sustained, intermittent or never achieving remission in patients with recent onset inflammatory polyarthritis:Results from the Norfolk Arthritis Register

Objectives: Early remission is the current treatment strategy for patients with inflammatory polyarthritis (IP) and RA. Our objective was to identify baseline factors associated with achieving remission: sustained (SR), intermittent (IR) or never (NR) over a 5-year period in patients with early IP.  Methods: Clinical and demographic data of patients with IP recruited to the Norfolk Arthritis Register (NOAR) were obtained at baseline and years 1, 2, 3 and 5. Remission was defined as no tender or swollen joints (out of 51). Patients were classified as NR or PR, respectively, if they were in remission at: no assessment or ⩾3 consecutive assessments after baseline, and IR otherwise. Ordinal regression and a random effects model, respectively, were used to examine the association between baseline factors, remission group and HAQ scores over time.  Results: A total of 868 patients (66% female) were included. Of these, 54%, 34% and 12% achieved NR, IR and SR, respectively. In multivariate analysis, female sex (odds ratio, OR 0.47, 95% CI: 0.35, 0.63), higher tender joint count (OR = 0.94, 95% CI: 0.93, 0.96), higher HAQ (OR = 0.59, 95% CI: 0.48, 0.74), being obese (OR = 0.70, 95% CI: 0.50, 0.99), hypertensive (OR = 0.67, 95% CI: 0.50, 0.90) or depressed (OR = 0.74, 95% CI: 0.55, 1.00) at baseline were independent predictors of being in a lower remission group. IR and SR were associated with lower HAQ scores over time and lower DAS28 at year 5.  Conclusion: Women with higher tender joint count and disability at baseline, depression, obesity and hypertension were less likely to achieve remission. This information could help when stratifying patients for more aggressive therapy

An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data

Emissions of methane (CH4) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH4 budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric CH4 columns can help to narrow down some of the uncertainties in the tropical CH4 emission budget. We use proxy column retrievals of atmospheric CH4 (XCH4) from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5 ∘ ×0.625 ∘ ) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH4 are less sensitive to scattering due to clouds and aerosol than full physics retrievals, but the method assumes that the global distribution of carbon dioxide (CO2) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH4 data products that are determined using different model CO2 fields. We infer monthly emissions from GOSAT XCH4 data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010 and 2016 range from 76 (74–78) to 80 (78–82) Tg yr−1, depending on the proxy XCH4 data used, with larger differences in Northern Hemisphere Africa than Southern Hemisphere Africa. We find a robust positive linear trend in tropical African CH4 emissions for our 7-year study period, with values of 1.5 (1.1–1.9) Tg yr−1 or 2.1 (1.7–2.5) Tg yr−1, depending on the CO2 data product used in the proxy retrieval. This linear emissions trend accounts for around a third of the global emissions growth rate during this period. A substantial portion of this increase is due to a short-term increase in emissions of 3 Tg yr−1 between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data, we find this increase in CH4 emissions is consistent with an increase in wetland extent due to increased inflow from the White Nile, although the data indicate that the Sudd was anomalously dry at the start of our inversion period. We find a strong seasonality in emissions across Northern Hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori CH4 emissions from the wetland area of the Congo Basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates

Harnessing repeated measurements of predictor variables for clinical risk prediction: a review of existing methods

From Springer Nature via Jisc Publications RouterHistory: received 2020-02-06, accepted 2020-04-28, registration 2020-04-28, pub-electronic 2020-07-09, online 2020-07-09, collection 2020-12Publication status: PublishedFunder: National Institute for Health Research; doi: http://dx.doi.org/10.13039/501100000272; Grant(s): DRF-2018-11-ST2-052Abstract: Background: Clinical prediction models (CPMs) predict the risk of health outcomes for individual patients. The majority of existing CPMs only harness cross-sectional patient information. Incorporating repeated measurements, such as those stored in electronic health records, into CPMs may provide an opportunity to enhance their performance. However, the number and complexity of methodological approaches available could make it difficult for researchers to explore this opportunity. Our objective was to review the literature and summarise existing approaches for harnessing repeated measurements of predictor variables in CPMs, primarily to make this field more accessible for applied researchers. Methods: MEDLINE, Embase and Web of Science were searched for articles reporting the development of a multivariable CPM for individual-level prediction of future binary or time-to-event outcomes and modelling repeated measurements of at least one predictor. Information was extracted on the following: the methodology used, its specific aim, reported advantages and limitations, and software available to apply the method. Results: The search revealed 217 relevant articles. Seven methodological frameworks were identified: time-dependent covariate modelling, generalised estimating equations, landmark analysis, two-stage modelling, joint-modelling, trajectory classification and machine learning. Each of these frameworks satisfies at least one of three aims: to better represent the predictor-outcome relationship over time, to infer a covariate value at a pre-specified time and to account for the effect of covariate change. Conclusions: The applicability of identified methods depends on the motivation for including longitudinal information and the method’s compatibility with the clinical context and available patient data, for both model development and risk estimation in practice

Comparative genomics of apomictic root-knot nematodes:Hybridization, ploidy, and dynamic genome change

The Root-Knot Nematodes (RKN; genus Meloidogyne) are important plant parasites causing substantial agricultural losses. The Meloidogyne incognita group (MIG) of species, most of which are obligatory apomicts (mitotic parthenogens), are extremely polyphagous and important problems for global agriculture. While understanding the genomic basis for their variable success on different crops could benefit future agriculture, analyses of their genomes are challenging due to complex evolutionary histories that may incorporate hybridization, ploidy changes, and chromosomal fragmentation. Here we sequence 19 genomes, representing five species of key RKN collected from different geographic origins. We show that a hybrid origin that predated speciation within the MIG has resulted in each species possessing two divergent genomic copies. Additionally, the apomictic MIG species are hypotriploids, with a proportion of one genome present in a second copy. The hypotriploid proportion varies among species. The evolutionary history of the MIG genomes is revealed to be very dynamic, with non-crossover recombination both homogenising the genomic copies, and acting as a mechanism for generating divergence between species. Interestingly, the automictic MIG species M. floridensis differs from the apomict species in that it has become homozygous throughout much of its genome

Validity of a three-variable juvenile arthritis disease activity score in children with new-onset juvenile idiopathic arthritis

<p>Objectives To investigate the validity and feasibility of the Juvenile Arthritis Disease Activity Score (JADAS) in the routine clinical setting for all juvenile idiopathic arthritis (JIA) disease categories and explore whether exclusion of the erythrocyte sedimentation rate (ESR) from JADAS (the ‘JADAS3’) influences correlation with single markers of disease activity.</p> <p>Methods JADAS-71, JADAS-27 and JADAS-10 were determined at baseline for an inception cohort of children with JIA in the Childhood Arthritis Prospective Study. JADAS3-71, JADAS3-27 and JADAS3-10 were determined using an identical formula but with exclusion of ESR. Correlation of JADAS with JADAS3 and single measures of disease activity/severity were determined by category.</p> <p>Results Of 956 eligible children, sufficient data were available to calculate JADAS-71, JADAS-27 and JADAS-10 at baseline in 352 (37%) and JADAS3 in 551 (58%). The median (IQR) JADAS-71, JADAS-27 and JADAS-10 for all 352 children was 11 (5.9–18), 10.4 (5.7–17) and 11 (5.9–17.3), respectively. Median JADAS and JADAS3 varied significantly with the category (Kruskal–Wallis p=0.0001), with the highest values in children with polyarticular disease patterns. Correlation of JADAS and JADAS3 across all categories was excellent. Correlation of JADAS71 with single markers of disease activity/severity was good to moderate, with some variation across the categories. With the exception of ESR, correlation of JADAS3-71 was similar to correlation of JADAS-71 with the same indices.</p> <p>Conclusions This study is the first to apply JADAS to all categories of JIA in a routine clinical setting in the UK, adding further information about the feasibility and construct validity of JADAS. For the majority of categories, clinical applicability would be improved by exclusion of the ESR.</p&gt

Anti-TNF therapy is associated with an increased risk of serious infections in patients with rheumatoid arthritis especially in the first 6 months of treatment: updated results from the British Society for Rheumatology Biologics Register with special emphasis on risks in the elderly

Objectives. To evaluate the risk of serious infections (SIs) in patients with RA treated with anti-TNF therapy with emphasis on the risk across different ages

Large-scale features of Pliocene climate: results from the Pliocene Model Intercomparison Project

Climate and environments of the mid-Pliocene warm period (3.264 to 3.025 Ma) have been extensively studied. Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a coordinated multi-model and multi-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are clearly evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data/model comparison highlights that models potentially underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Furthermore, sensitivity tests exploring the known unknowns in modelling Pliocene climate specifically relevant to the high latitudes are essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses). Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS), support previous work suggesting that ESS is greater than Climate Sensitivity (CS), and suggest that the ratio of ESS to CS is between 1 and 2, with a "best" estimate of 1.5

Genetic drift, not life history or RNAi, determine long term evolution of transposable elements

Transposable elements (TEs) are a major source of genome variation across the branches of life. Although TEs may play an adaptive role in their host’s genome, they are more often deleterious, and purifying selection is an important factor controlling their genomic loads. In contrast, life history, mating system, GC content, and RNAi pathways, have been suggested to account for the disparity of TE loads in different species. Previous studies of fungal, plant, and animal genomes have reported conflicting results regarding the direction in which these genomic features drive TE evolution. Many of these studies have had limited power, however, because they studied taxonomically narrow systems, comparing only a limited number of phylogenetically independent contrasts, and did not address long-term effects on TE evolution. Here we test the long-term determinants of TE evolution by comparing 42 nematode genomes spanning over 500 million years of diversification. This analysis includes numerous transitions between life history states, and RNAi pathways, and evaluates if these forces are sufficiently persistent to affect the long-term evolution of TE loads in eukaryotic genomes. Although we demonstrate statistical power to detect selection, we find no evidence that variation in these factors influence genomic TE loads across extended periods of time. In contrast, the effects of genetic drift appear to persist and control TE variation among species. We suggest that variation in the tested factors are largely inconsequential to the large differences in TE content observed between genomes, and only by these large-scale comparisons can we distinguish long-term and persistent effects from transient or random changes

Differential Drug Survival of Biologic Therapies for the Treatment of Psoriasis: A Prospective Observational Cohort Study from the British Association of Dermatologists Biologic Interventions Register (BADBIR)

Drug survival reflects a drug’s effectiveness, safety, and tolerability. We assessed the drug survival of biologics used to treat psoriasis in a prospective national pharmacovigilance cohort (British Association of Dermatologists Biologic Interventions Register (BADBIR)). The survival rates of the first course of biologics for 3,523 biologic-naive patients with chronic plaque psoriasis were compared using survival analysis techniques and predictors of discontinuation analyzed using a multivariate Cox proportional hazards model. Data for patients on adalimumab (n=1,879), etanercept (n=1,098), infliximab (n=96), and ustekinumab (n=450) were available. The overall survival rate in the first year was 77%, falling to 53% in the third year. Multivariate analysis showed that female gender (hazard ratio (HR) 1.22; 95% confidence interval (CI): 1.09–1.37), being a current smoker (HR 1.19; 95% CI: 1.03–1.38), and a higher baseline dermatology life quality index (HR 1.01; 95% CI: 1.00–1.02) were predictors of discontinuation. Presence of psoriatic arthritis (HR 0.82; 95% CI: 0.71–0.96) was a predictor for drug survival. As compared with adalimumab, patients on etanercept (HR 1.63; 95% CI: 1.45–1.84) or infliximab (HR 1.56; 95% CI: 1.16–2.09) were more likely to discontinue therapy, whereas patients on ustekinumab were more likely to persist (HR 0.48; 95% CI: 0.37–0.62). After accounting for relevant covariates, ustekinumab had the highest first-course drug survival. The results of this study will aid clinical decision making when choosing biologic therapy for psoriasis patients