Glucocorticoids, secreted by the adrenals in response to stress, profoundly affect structure and plasticity of neurons. Glucocorticoid action in neurons is mediated by glucocorticoid receptors (GR) ...that operate as transcription factors in the regulation of gene expression and either bind directly to genomic glucocorticoid response elements (GREs) or indirectly to the genome via interactions with bound transcription factors. These two modes of action, respectively called transactivation and transrepression, result in the regulation of a wide variety of genes important for neuronal function. The objective of the present study was to identify genome-wide glucocorticoid receptor binding sites in neuronal PC12 cells using Chromatin ImmunoPrecipitation combined with next generation sequencing (ChIP-Seq).
In total we identified 1183 genomic binding sites of GR, the majority of which were novel and not identified in other ChIP-Seq studies on GR binding. More than half (58%) of the binding sites contained a GRE. The remaining 42% of the GBS did not harbour a GRE and therefore likely bind GR via an intermediate transcription factor tethering GR to the DNA. While the GRE-containing binding sites were more often located nearby genes involved in general cell functions and processes such as apoptosis, cell motion, protein dimerization activity and vasculature development, the binding sites without a GRE were located nearby genes with a clear role in neuronal processes such as neuron projection morphogenesis, neuron projection regeneration, synaptic transmission and catecholamine biosynthetic process. A closer look at the sequence of the GR binding sites revealed the presence of several motifs for transcription factors that are highly divergent from those previously linked to GR-signaling, including Gabpa, Prrx2, Zfp281, Gata1 and Zbtb3. These transcription factors may represent novel crosstalk partners of GR in a neuronal context.
Here we present the first genome-wide inventory of GR-binding sites in a neuronal context. These results provide an exciting first global view into neuronal GR targets and the neuron-specific modes of GR action and potentially contributes to our understanding of glucocorticoid action in the brain.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Macrophages constitute important immune cell targets of the antifolate methotrexate (MTX) in autoimmune diseases, including rheumatoid arthritis. Regulation of folate/MTX metabolism remains poorly ...understood upon pro-inflammatory (M1-type/GM-CSF-polarized) and anti-inflammatory (M2-type/M-CSF-polarized) macrophages. MTX activity strictly relies on the folylpolyglutamate synthetase (FPGS) dependent intracellular conversion and hence retention to MTX-polyglutamate (MTX-PG) forms. Here, we determined FPGS pre-mRNA splicing, FPGS enzyme activity and MTX-polyglutamylation in human monocyte-derived M1- and M2-macrophages exposed to 50 nmol/L MTX ex vivo. Moreover, RNA-sequencing analysis was used to investigate global splicing profiles and differential gene expression in monocytic and MTX-exposed macrophages. Monocytes displayed six-eight-fold higher ratios of alternatively-spliced/wild type FPGS transcripts than M1- and M2-macrophages. These ratios were inversely associated with a six-ten-fold increase in FPGS activity in M1- and M2-macrophages versus monocytes. Total MTX-PG accumulation was four-fold higher in M1- versus M2-macrophages. Differential splicing after MTX-exposure was particularly apparent in M2-macrophages for histone methylation/modification genes. MTX predominantly induced differential gene expression in M1-macrophages, involving folate metabolic pathway genes, signaling pathways, chemokines/cytokines and energy metabolism. Collectively, macrophage polarization-related differences in folate/MTX metabolism and downstream pathways at the level of pre-mRNA splicing and gene expression may account for variable accumulation of MTX-PGs, hence possibly impacting MTX treatment efficacy.
•Accurate queueing network capturing performance of real-world laboratory systems.•Centralized decision maker that optimizes static routes minimizing mean turnaround time.•Combined Queueing Network ...Analyzer and Simulated Annealing approach.•Approach applicable to networks of FIFO queues with general service and inter-arrival times.•Optimal design of clinical chemistry laboratories.
This paper considers optimal design of queueing networks in which each node consists of a single-server FIFO queue and an infinite-server queue, which is referred to as incubation queue. Upon service completion at a FIFO queue, a job splits (forks) into two parts: the first part is routed to the next node on its route, and the second part is placed in the incubation queue. Routing of the jobs of multiple types is governed by a central decision maker that decides on the routes for each job type and aims to minimize the mean turnaround time of the jobs, i.e., the time spent in the system until service completion at the FIFO queue in the last node, and at all incubation queues on the job’s route, which may be viewed as a join operation. We provide explicit results for the turnaround time when all service and inter-arrival time distributions are exponential and invoke the Queueing Network Analyzer when these distributions are general. We then develop a Simulated Annealing approach to find the optimal routing configuration. We apply our approach to determine the optimal routing configuration in a chemistry analyzer line.
LINKED CONTENT
This article is linked to van de Meeberg et al papers. To view these articles, visit https://doi.org/10.1111/apt.17719 and https://doi.org/10.1111/apt.17743
Aims
In immune‐mediated inflammatory diseases (IMIDs), early symptom control is a key therapeutic goal. Methotrexate (MTX) is the first‐line treatment across IMIDs. However, MTX is underutilized and ...suboptimally dosed, partly due to the inability of making individualized treatment decisions through therapeutic drug monitoring (TDM). To implement TDM in clinical practice, establishing a relationship between drug concentration and disease activity is paramount. In this meta‐analysis, we investigated the relationship between concentrations of MTX polyglutamates (MTX‐PG) in erythrocytes and efficacy as well as toxicity across IMIDs.
Methods
Studies analysing MTX‐PG in relation to disease activity and/or toxicity were included for inflammatory arthritis (rheumatoid RA and juvenile idiopathic arthritis JIA), inflammatory bowel disease (Crohn's and ulcerative colitis) and dermatitis (psoriasis and atopic dermatitis). Meta‐analyses were performed resulting in several summary effect measures: regression coefficient (β), correlation coefficient and mean difference (of MTX‐PG in responders vs. nonresponders) for IMIDs separately and collectively.
Results
Twenty‐five studies were included. In RA and JIA, higher MTX‐PG was significantly associated with lower disease activity at 3 months (β: −0.002; 95% confidence interval CI: −0.004 to −0.001) and after 4 months of MTX use (β: −0.003; 95% CI: −0.005 to −0.002). Similarly, higher MTX‐PG correlated with lower disease activity in psoriasis (R: −0.82; 95% CI: −0.976 to −0.102). Higher MTX‐PG was observed in RA, JIA and psoriasis responders (mean difference: 5.2 nmol/L MTX‐PGtotal; P < .01).
Conclusion
We showed that higher concentrations of erythrocyte MTX‐PG were associated with lower disease activity in RA, JIA and psoriasis. These findings are an important step towards implementation of TDM for MTX treatment across IMIDs.
Methotrexate polyglutamates (MTX‐PG) concentrations in red blood cells (RBCs) have been suggested as a biomarker of response in patients with rheumatoid arthritis (RA) receiving low‐dose MTX therapy. ...We investigated the association and interpatient variability between RBC‐MTX‐PG3‐5‐exposure and response in patients with RA starting MTX. Data of three prospective cohorts were available. The relationship between exposure and Disease Activity Score in 28 joints (DAS28) was analyzed using a population pharmacokinetic‐pharmacodynamic model. Relevant covariates were tested using full covariate modeling and backward elimination. From 395 patients, 3,401 MTX‐PG concentrations and 1,337 DAS28 measurements were available between 0 and 300 days after MTX treatment onset. The developed model adequately described the time course of MTX‐PG3‐5 and DAS28. The median MTX‐PG3‐5 level at month 1 was 30.9 nmol/L (interquartile range (IQR): 23.6–43.7; n = 41) and at month 3: 69.3 nmol/L (IQR: 17.9–41.2; n = 351). Clearance of MTX‐PG3‐5 from RBCs was 28% lower (95% confidence interval (CI): 23.6–32.8%) in a woman and 10% lower (95% CI: 7.7–12.4%) in a 65‐year‐old compared with a 35‐year‐old patient. MTX‐PG3‐5 concentrations associated with DAS28: half‐maximal effective concentration (EC50) was 9.14 nmol/L (95% CI: 4.2 nmol/L‐14.1 nmol/L). EF at 80% (EC80) above 47 nmol/L was regarded as the optimal response. Independent of the MTX‐PG 3–5 – response association, co‐administration of disease‐modifying antirheumatic drugs and corticosteroids improved response (additive effect on maximum effect (Emax)), whereas smoking, high body mass index and low albumin decreased Emax. In patients with RA starting MTX, RBC‐MTX‐PG3‐5 was associated with clinical response. A dose increase is suggested when MTX‐PG3‐5 at month 1 is below 9.15 nmol/L, continued with the same dose when the concentration is above 47 nmol/L, and consider other treatment options above 78 nmol/L from 3 months onwards.
Abstract
Context
Newborn screening (NBS) for classic congenital adrenal hyperplasia (CAH) consists of 17-hydroxyprogesterone (17-OHP) measurement with gestational age–adjusted cutoffs. A second heel ...puncture (HP) is performed in newborns with inconclusive results to reduce false positives.
Objective
We assessed the accuracy and turnaround time of the current CAH NBS algorithm in comparison with alternative algorithms by performing a second-tier 21-deoxycortisol (21-DF) pilot study.
Methods
Dried blood spots (DBS) of newborns with inconclusive and positive 17-OHP (immunoassay) first HP results were sent from regional NBS laboratories to the Amsterdam UMC Endocrine Laboratory. In 2017-2019, 21-DF concentrations were analyzed by LC-MS/MS in parallel with routine NBS. Diagnoses were confirmed by mutation analysis.
Results
A total of 328 DBS were analyzed; 37 newborns had confirmed classic CAH, 33 were false-positive and 258 were categorized as negative in the second HP following the current algorithm. With second-tier testing, all 37 confirmed CAH had elevated 21-DF, while all 33 false positives and 253/258 second-HP negatives had undetectable 21-DF. The elevated 21-DF of the other 5 newborns may be NBS false negatives or second-tier false positives. Adding the second-tier results to inconclusive first HPs reduced the number of false positives to 11 and prevented all 286 second HPs. Adding the second tier to both positive and inconclusive first HPs eliminated all false positives but delayed referral for 31 CAH patients (1-4 days).
Conclusion
Application of the second-tier 21-DF measurement to inconclusive first HPs improved our CAH NBS by reducing false positives, abolishing the second HP, and thereby shortening referral time.
The objective was to predict insufficient response to 3 months methotrexate (MTX) in DMARD naïve rheumatoid arthritis patients.
A Multivariable logistic regression model of rheumatoid arthritis ...patients starting MTX was developed in a derivation cohort with 285 patients starting MTX in a clinical multicentre, stratified single-blinded trial, performed in seven secondary care clinics and a tertiary care clinic. The model was validated in a validation cohort with 102 patients starting MTX at a tertiary care clinic. Outcome was insufficient response (disease activity score (DAS)28 >3.2) after 3 months of MTX treatment. Clinical characteristics, lifestyle variables, genetic and metabolic biomarkers were determined at baseline in both cohorts. These variables were dichotomized and used to construct a multivariable prediction model with backward logistic regression analysis.
The prediction model for insufficient response in the derivation cohort, included: DAS28>5.1, Health Assessment Questionnaire>0.6, current smoking, BMI>25 kg/m2, ABCB1 rs1045642 genotype, ABCC3 rs4793665 genotype, and erythrocyte-folate<750 nmol/L. In the derivation cohort, AUC of ROC curve was 0.80 (95%CI: 0.73-0.86), and 0.80 (95%CI: 0.69-0.91) in the validation cohort. Betas of the prediction model were transformed into total risk score (range 0-8). At cutoff of ≥4, probability for insufficient response was 44%. Sensitivity was 71%, specificity 72%, with positive and negative predictive value of 72% and 71%.
A prognostics prediction model for insufficient response to MTX in 2 prospective RA cohorts by combining genetic, metabolic, clinical and lifestyle variables was developed and validated. This model satisfactorily identified RA patients with high risk of insufficient response to MTX.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
Computational tools analyzing RNA-sequencing data have boosted alternative splicing research by identifying and assessing differentially spliced genes. However, common alternative ...splicing analysis tools differ substantially in their statistical analyses and general performance. This report compares the computational performance (CPU utilization and RAM usage) of three event-level splicing tools; rMATS, MISO, and SUPPA2. Additionally, concordance between tool outputs was investigated.
Results
Log-linear relations were found between job times and dataset size in all splicing tools and all virtual machine (VM) configurations. MISO had the highest job times for all analyses, irrespective of VM size, while MISO analyses also exceeded maximum CPU utilization on all VM sizes. rMATS and SUPPA2 load averages were relatively low in both size and replicate comparisons, not nearing maximum CPU utilization in the VM simulating the lowest computational power (D2 VM). RAM usage in rMATS and SUPPA2 did not exceed 20% of maximum RAM in both size and replicate comparisons while MISO reached maximum RAM usage in D2 VM analyses for input size. Correlation coefficients of differential splicing analyses showed high correlation (β > 80%) between different tool outputs with the exception of comparisons of retained intron (RI) events between rMATS/MISO and rMATS/SUPPA2 (β < 60%).
Conclusions
Prior to RNA-seq analyses, users should consider job time, amount of replicates and splice event type of interest to determine the optimal alternative splicing tool. In general, rMATS is superior to both MISO and SUPPA2 in computational performance. Analysis outputs show high concordance between tools, with the exception of RI events.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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