Objectives To explore the relationship of serious infection risk with current and prior oral glucocorticoid (GC) therapy in elderly patients with rheumatoid arthritis (RA). Methods A case-control analysis matched 1947 serious infection cases to fi ve controls, selected from 16207 RA patients aged ≥65 between 1985-2003 in Quebec, Canada. Adjusted odds ratios for infection associated with different GC patterns were estimated using conventional models and a weighted cumulative dose (WCD) model. Results The WCD model predicted risks better than conventional models. Current and recent GC doses had highest impact on current risk. Doses taken up to 2.5 years ago were also associated with increased risk, albeit to a lesser extent. A current user of 5mg prednisolone had a 30%, 46% or 100% increased risk of serious infection when used continuously for the last 3 months, 6 months or 3 years, respectively, compared to a non-user. The risk associated with 5mg prednisolone taken for the last 3 years was similar to that associated with 30mg taken for the last month. Discontinuing a two-year course of 10mg prednisolone six months ago halved the risk compared to ongoing use. Conclusions GC therapy is associated with infection risk in older patients with RA. The WCD model provided more accurate risk estimates than conventional models. Current and recent doses have greatest impact on infection risk, but the cumulative impact of doses taken in the last 2-3 years still affects risk. Knowing how risk depends on pattern of GC use will contribute to an improved benefi t/harm assessment.

Pharmacoepidemiology investigates associations between time-varying medication use/dose and risk of adverse events. Applied research typically relies on a priori chosen simple conventional models, such as current dose or any use in the past 3 months. However, different models imply different risk predictions, and only one model can be etiologically correct in any specific applications. We first formally defined several candidate models mapping the time vector of past drug doses (X (t), t  =  1, … ,u) into the value of a time-varying exposure metric M(u) at current time u. In addition to conventional one-parameter models, we considered two-parameter models accounting for recent dose increase or withdrawal and a flexible spline-based weighted cumulative exposure (WCE) model that defines M(u) as the weighted sum of past doses. In simulations, we generated event times assuming one of the models was correct and then analyzed the data with all candidate models. We demonstrated that the minimum AIC criterion is able to identify the correct model as the best-fitting model or one of the equivalent (within 4 AIC points of the minimum) models in a vast majority of simulated samples, especially with 500 or more events. We also showed how relying on an incorrect a priori chosen model may largely reduce the power to test for an association. Finally, we demonstrated how the flexible WCE estimates may help with model diagnostics even if the correct model is not WCE. We illustrated the practical advantages of AIC-based a posteriori model selection and WCE modeling in a real-life pharmacoepidemiology example.

ObjectiveTo quantify the risk of incident diabetes mellitus (DM) associated with the dosage, duration, and timing of glucocorticoid (GC) use in patients with rheumatoid arthritis (RA).MethodsWe undertook a cohort study using 2 databases: a UK primary care database (the Clinical Practice Research Datalink [CPRD]) including 21,962 RA patients (1992–2009) and the US National Data Bank for Rheumatic Diseases (NDB) including 12,657 RA patients (1998–2013). Information on the dosage and timing of GC use was extracted. DM in the CPRD was defined using Read codes, at least 2 prescriptions for oral antidiabetic medication, or abnormal blood test results. DM in the NDB was defined through patient self‐reports. Data were analyzed using time‐dependent Cox models and a novel weighted cumulative dose (WCD) model that accounts for dosage, duration, and timing of treatment.ResultsThe hazard ratio (HR) was 1.30 (95% confidence interval [95% CI] 1.17–1.45) and 1.61 (95% CI 1.37–1.89) in current GC users compared to nonusers in the CPRD and the NDB, respectively. A range of conventional statistical models consistently confirmed increases in risk with the GC dosage and duration. The WCD model showed that recent GC use contributed the most to the current risk of DM, while doses taken >6 months previously did not influence current risk. In the CPRD, 5 mg of prednisolone equivalent dose for the last 1, 3, and 6 months was significantly associated with HRs of 1.20, 1.43, and 1.48, respectively, compared to nonusers.ConclusionGC use is a clinically important and quantifiable risk factor for DM. Risk is influenced by the dosage and treatment duration, although only for GC use within the last 6 months.

Anterior gradient 2 ( AGR 2) is a dimeric protein disulfide isomerase family member involved in the regulation of protein quality control in the endoplasmic reticulum ( ER ). Mouse AGR 2 deletion increases intestinal inflammation and promotes the development of inflammatory bowel disease ( IBD ). Although these biological effects are well established, the underlying molecular mechanisms of AGR 2 function toward inflammation remain poorly defined. Here, using a protein–protein interaction screen to identify cellular regulators of AGR 2 dimerization, we unveiled specific enhancers, including TMED 2, and inhibitors of AGR 2 dimerization, that control AGR 2 functions. We demonstrate that modulation of AGR 2 dimer formation, whether enhancing or inhibiting the process, yields pro‐inflammatory phenotypes, through either autophagy‐dependent processes or secretion of AGR 2, respectively. We also demonstrate that in IBD and specifically in Crohn's disease, the levels of AGR 2 dimerization modulators are selectively deregulated, and this correlates with severity of disease. Our study demonstrates that AGR 2 dimers act as sensors of ER homeostasis which are disrupted upon ER stress and promote the secretion of AGR 2 monomers. The latter might represent systemic alarm signals for pro‐inflammatory responses.

Background CRISPR-Cas9 gene-editing technology has facilitated the generation of knockout mice, providing an alternative to cumbersome and time-consuming traditional embryonic stem cell-based methods. An earlier study reported up to 16% efficiency in generating conditional knockout (cKO or floxed) alleles by microinjection of 2 single guide RNAs (sgRNA) and 2 single-stranded oligonucleotides as donors (referred herein as “two-donor floxing” method). Results We re-evaluate the two-donor method from a consortium of 20 laboratories across the world. The dataset constitutes 56 genetic loci, 17,887 zygotes, and 1718 live-born mice, of which only 15 (0.87%) mice contain cKO alleles. We subject the dataset to statistical analyses and a machine learning algorithm, which reveals that none of the factors analyzed was predictive for the success of this method. We test some of the newer methods that use one-donor DNA on 18 loci for which the two-donor approach failed to produce cKO alleles. We find that the one-donor methods are 10- to 20-fold more efficient than the two-donor approach. Conclusion We propose that the two-donor method lacks efficiency because it relies on two simultaneous recombination events in cis , an outcome that is dwarfed by pervasive accompanying undesired editing events. The methods that use one-donor DNA are fairly efficient as they rely on only one recombination event, and the probability of correct insertion of the donor cassette without unanticipated mutational events is much higher. Therefore, one-donor methods offer higher efficiencies for the routine generation of cKO animal models. Electronic supplementary material The online version of this article (10.1186/s13059-019-1776-2) contains supplementary material, which is available to authorized users.