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Objective: There is growing evidence that genetic data are of benefit in the rheumatology outpatient setting by aiding early diagnosis. A genetic probability tool (G‐PROB) has been developed to aid diagnosis has not yet been tested in a real‐world setting. Our aim was to assess whether G‐PROB could aid diagnosis in the rheumatology outpatient setting using data from the Norfolk Arthritis Register (NOAR), a prospective observational cohort of patients presenting with early inflammatory arthritis. Methods: Genotypes and clinician diagnoses were obtained from patients from NOAR. Six G‐probabilities (0%–100%) were created for each patient based on known disease‐associated odds ratios of published genetic risk variants, each corresponding to one disease of rheumatoid arthritis, systemic lupus erythematosus, psoriatic arthritis, spondyloarthropathy, gout, or "other diseases." Performance of the G‐probabilities compared with clinician diagnosis was assessed. Results: We tested G‐PROB on 1,047 patients. Calibration of G‐probabilities with clinician diagnosis was high, with regression coefficients of 1.047, where 1.00 is ideal. G‐probabilities discriminated clinician diagnosis with pooled areas under the curve (95% confidence interval) of 0.85 (0.84–0.86). G‐probabilities <5% corresponded to a negative predictive value of 96.0%, for which it was possible to suggest >2 unlikely diseases for 94% of patients and >3 for 53.7% of patients. G‐probabilities >50% corresponded to a positive predictive value of 70.4%. In 55.7% of patients, the disease with the highest G‐probability corresponded to clinician diagnosis. Conclusion: G‐PROB converts complex genetic information into meaningful and interpretable conditional probabilities, which may be especially helpful at eliminating unlikely diagnoses in the rheumatology outpatient setting. [ABSTRACT FROM AUTHOR]

Objective: We undertook this study to estimate changes in cell‐specific DNA methylation (DNAm) associated with methotrexate (MTX) response using whole blood samples collected from rheumatoid arthritis (RA) patients before and after initiation of MTX treatment. Methods: Patients included in this study were from the Rheumatoid Arthritis Medication Study (n = 66) and the University of California San Francisco Rheumatoid Arthritis study (n = 11). All patients met the American College of Rheumatology RA classification criteria. Blood samples were collected at baseline and following treatment. Disease Activity Scores in 28 joints using the C‐reactive protein level were collected at baseline and after 3–6 months of treatment with MTX. Methylation profiles were generated using the Illumina Infinium HumanMethylation450 and MethylationEPIC v1.0 BeadChip arrays using DNA from whole blood. MTX response was defined using the EULAR response criteria (responders showed good/moderate response; nonresponders showed no response). Differentially methylated positions were identified using the Limma software package and Tensor Composition Analysis, which is a method for identifying cell‐specific differential DNAm at the CpG level from tissue‐level ("bulk") data. Differentially methylated regions were identified using Comb‐p software. Results: We found evidence of differential global methylation between treatment response groups. Further, we found patterns of cell‐specific differential global methylation associated with MTX response. After correction for multiple testing, 1 differentially methylated position was associated with differential DNAm between responders and nonresponders at baseline in CD4+ T cells, CD8+ T cells, and natural killer cells. Thirty‐nine cell‐specific differentially methylated regions associated with MTX treatment response were identified. There were no significant findings in analyses of whole blood samples. Conclusion: We identified cell‐specific changes in DNAm that were associated with MTX treatment response in RA patients. Future studies of DNAm and MTX treatment response should include measurements of DNAm from sorted cells. [ABSTRACT FROM AUTHOR]

Hepatotoxicity is a serious adverse drug reaction related to methotrexate (MTX). However, the cause of drug‐induced liver injury (DILI) is still unclear and unpredictable. Genetic risk factors may predispose for MTX‐DILI. Therefore, we conducted a nested case‐control genome‐wide association study to explore genetic risk factors associated with MTX‐DILI. Seven international groups contributed blood samples and data of patients with rheumatoid arthritis who used MTX. MTX‐DILI was defined as an alanine aminotransferase (ALT) level of at least three times the upper limit of normal (ULN), to increase contrast controls ALT levels did not raise above two times the ULN. Per study site, control subjects and patients with MTX‐DILI (ratio 3:1) were matched for age, gender, and duration of MTX use. Patients were genotyped using Illumina GSA MD‐24v1‐0 and data were imputed using the 1000 Genomes reference panel. Single‐nucleotide polymorphisms (SNPs) were analyzed using an additive genetic model, corrected for sex, country, and age. A P‐value of ≤ 5 × 10−8 was considered significant, whereas a P‐value of ≤ 5 × 10−6 was considered suggestive. A total of 108 MTX‐DILI cases and 311 controls were included for association analysis. None of the SNPs were significantly associated with MTX‐DILI. However, we found seven suggestive genetic variants associated with MTX‐DILI (P‐values 7.43 × 10−8 to 4.86 × 10−6). Of those, five SNPs were in the intronic protein‐coding regions of FTCDNL1, BCOR, FGF14, RBMS3, and PFDN4/DOK5. Investigation of candidates SPATA9 (rs72783407), PLCG2 (rs60427389), RAVER2 (rs72675408), JAK1 (rs72675451), PTPN2 (rs2476601), MTHFR C677T (rs1801133), and into the HLA region did not show significant findings. No genetic variants associated with MTX‐DILI were found, whereas suggestive SNPs need further investigation. [ABSTRACT FROM AUTHOR]

Objective: To determine whether using a reweighted disease activity score that better reflects joint synovitis, i.e., the 2‐component Disease Activity Score in 28 joints (DAS28) (based on swollen joint count and C‐reactive protein level), produces more clinically relevant treatment outcome trajectories compared to the standard 4‐component DAS28. Methods: Latent class mixed modeling of response to biologic treatment was applied to 2,991 rheumatoid arthritis (RA) patients in whom treatment with a biologic disease‐modifying antirheumatic drug was being initiated within the Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate cohort, using both 4‐component and 2‐component DAS28 scores as outcome measures. Patient groups with similar trajectories were compared in terms of pretreatment baseline characteristics (including disability and comorbidities) and follow‐up characteristics (including antidrug antibody events, adherence to treatments, and blood drug levels). We compared the trajectories obtained using the 4‐ and 2‐component scores to determine which characteristics were better captured by each. Results: Using the 4‐component DAS28, we identified 3 trajectory groups, which is consistent with previous findings. We showed that the 4‐component DAS28 captures information relating to depression. Using the 2‐component DAS28, 7 trajectory groups were identified; among them, distinct groups of nonresponders had a higher incidence of respiratory comorbidities and a higher proportion of antidrug antibody events. We also identified a group of patients for whom the 2‐component DAS28 scores remained relatively low; this group included a high percentage of patients who were nonadherent to treatment. This highlights the utility of both the 4‐ and 2‐component DAS28 for monitoring different components of disease activity. Conclusion: Here we show that the 2‐component modified DAS28 defines important biologic and clinical phenotypes associated with treatment outcome in RA and characterizes important underlying response mechanisms to biologic drugs. [ABSTRACT FROM AUTHOR]

Objective: Approximately 30–40% of rheumatoid arthritis (RA) patients who are initially started on low‐dose methotrexate (MTX) will not benefit from the treatment. To date, no reliable biomarkers of MTX inefficacy in RA have been identified. The aim of this study was to analyze whole blood samples from RA patients at 2 time points (pretreatment and 4 weeks following initiation of MTX), to identify gene expression biomarkers of the MTX response. Methods: RA patients who were about to commence treatment with MTX were selected from the Rheumatoid Arthritis Medication Study. Using European League Against Rheumatism (EULAR) response criteria, 42 patients were categorized as good responders and 43 as nonresponders at 6 months following the initation of MTX treatment. Data on whole blood transcript expression were generated, and supervised machine learning methods were used to predict a EULAR nonresponse. Models in which transcript levels were included were compared to models in which clinical covariates alone (e.g., baseline disease activity, sex) were included. Gene network and ontology analysis was also performed. Results: Based on the ratio of transcript values (i.e., the difference in log2‐transformed expression values between 4 weeks of treatment and pretreatment), a highly predictive classifier of MTX nonresponse was developed using L2‐regularized logistic regression (mean ± SEM area under the receiver operating characteristic [ROC] curve [AUC] 0.78 ± 0.11). This classifier was superior to models that included clinical covariates (ROC AUC 0.63 ± 0.06). Pathway analysis of gene networks revealed significant overrepresentation of type I interferon signaling pathway genes in nonresponders at pretreatment (P = 2.8 × 10−25) and at 4 weeks after treatment initiation (P = 4.9 × 10−28). Conclusion: Testing for changes in gene expression between pretreatment and 4 weeks post–treatment initiation may provide an early classifier of the MTX treatment response in RA patients who are unlikely to benefit from MTX over 6 months. Such patients should, therefore, have their treatment escalated more rapidly, which would thus potentially impact treatment pathways. These findings emphasize the importance of a role for early treatment biomarker monitoring in RA patients started on MTX. [ABSTRACT FROM AUTHOR]

Novel hybrid molecules were synthesized through the amalgamation of quinoxaline residue with 1,3,4‐oxadiazole molecule. The purity of obtained 1,3,4‐oxadiazoles derivatives containing quinoxaline residue (total 11) was confirmed through thin‐layer chromatography, combustion analysis, and melting point, whereas their structures were confirmed by infrared spectroscopy, nuclear magnetic resonance, and mass spectroscopy. In animal studies, the derivatives 4‐(5‐(4‐(3‐methylquinoxalin‐2‐yl)phenyl)‐1,3,4‐oxadiazol‐2‐yl)benzenamine and 2‐(5‐(4‐(3‐methylquinoxalin‐2‐yl)phenyl)‐1,3,4‐oxadiazol‐2‐yl)benzenamine showed excellent analgesic and anti‐inflammatory activities, respectively, as compared with other derivatives. In order to rationalize the biological results of the derivatives, molecular docking studies were performed using Argus lab. The compounds exhibited good docking scores between −12.987 and −9.92 kcal/mol against cyclooxygenase‐II (5IKQ) protein fragment. [ABSTRACT FROM AUTHOR]

Objective: Rheumatoid arthritis (RA) is a genetically complex disease of immune dysregulation. This study sought to gain further insight into the genetic risk mechanisms of RA by conducting an expression quantitative trait locus (eQTL) analysis of confirmed genetic risk loci in CD4+ T cells and B cells from carefully phenotyped patients with early arthritis who were naive to therapeutic immunomodulation. Methods: RNA and DNA were isolated from purified B and/or CD4+ T cells obtained from the peripheral blood of 344 patients with early arthritis. Genotyping and global gene expression measurements were carried out using Illumina BeadChip microarrays. Variants in linkage disequilibrium (LD) with non‐HLA RA single‐nucleotide polymorphisms (defined as r2 ≥ 0.8) were analyzed, seeking evidence of cis‐ or trans‐eQTLs according to whether the associated probes were or were not within 4 Mb of these LD blocks. Results: Genes subject to cis‐eQTL effects that were common to both CD4+ and B lymphocytes at RA risk loci were FADS1, FADS2, BLK, FCRL3, ORMDL3, PPIL3, and GSDMB. In contrast, those acting on METTL21B, JAZF1, IKZF3, and PADI4 were unique to CD4+ lymphocytes, with the latter candidate risk gene being identified for the first time in this cell subset. B lymphocyte–specific eQTLs for SYNGR1 and CD83 were also found. At the 8p23 BLK–FAM167A locus, adjacent genes were subject to eQTLs whose activity differed markedly between cell types; in particular, the FAM167A effect displayed striking B lymphocyte specificity. No trans‐eQTLs approached experiment‐wide significance, and linear modeling did not identify a significant influence of biologic covariates on cis‐eQTL effect sizes. Conclusion: These findings further refine the understanding of candidate causal genes in RA pathogenesis, thus providing an important platform from which downstream functional studies, directed toward particular cell types, may be prioritized. [ABSTRACT FROM AUTHOR]

Introduction: Single- and multiple-fraction external beam radiotherapy (SFX-EBRT and MFX-EBRT) are palliative treatment options for localized metastatic bone pain. MFX is the preferred choice in many developed countries. Evidence shows little difference in how effectively SFX and MFX reduce pain. However, SFX is associated with higher retreatment and (in one meta-analysis) pathological fracture rates. MFX is, however, more time-consuming and expensive. We estimated the cost-effectiveness of SFX versus MFX for metastatic bone pain in breast, prostate and lung cancer in New Zealand.Methods: We constructed a Markov microsimulation model to estimate health gain (in quality-adjusted life-years or QALYs), health system costs (in real 2011 NZ dollars) and cost-effectiveness. The model was populated using effect estimates from randomized controlled trials and other studies, and New Zealand cancer and cost data. Disability weights from the 2010 Global Burden of Disease study were used in estimating QALYs.Results: Across all three cancers, QALY gains were similar for SFX compared to MFX, and per patient costs were less for SFX than MFX, with a difference of NZ$1469 (95% uncertainty interval $1112 to $1886) for lung cancer, $1316 ($810 to $1854) for prostate cancer and $1344 ($855 to $1846) for breast cancer. Accordingly, from a cost-effectiveness perspective, SFX was the preferable treatment option. Various sensitivity analyses did not overturn the clear preference for SFX.Conclusion: For all three cancers, SFX was clearly more cost-effective than MFX. This adds to the case for desisting from offering MFX to patients with metastatic bone pain, from a cost-effectiveness angle. [ABSTRACT FROM AUTHOR]

Objective Biologic drug therapies represent a huge advance in the treatment of rheumatoid arthritis (RA). However, very good disease control is achieved in only 30% of patients, making identification of biomarkers of response a research priority. We undertook this study to test our hypothesis that differential DNA methylation patterns may provide biomarkers predictive of response to tumor necrosis factor inhibitor (TNFi) therapy in patients with RA. Methods An epigenome-wide association study was performed on pretreatment whole blood DNA from patients with RA. Patients who displayed good response (n = 36) or no response (n = 36) to etanercept therapy at 3 months were selected. Differentially methylated positions were identified using linear regression. Variance of methylation at differentially methylated positions was assessed for correlation with cis-acting single-nucleotide polymorphisms (SNPs). A replication experiment for prioritized SNPs was performed in an independent cohort of 1,204 RA patients. Results Five positions that were differentially methylated between responder groups were identified, with a false discovery rate of <5%. The top 2 differentially methylated positions mapped to exon 7 of the LRPAP1 gene on chromosome 4 (cg04857395, P = 1.39 × 10−8 and cg26401028, P = 1.69 × 10−8). The A allele of the SNP rs3468 was correlated with higher levels of methylation for both of the top 2 differentially methylated positions ( P = 2.63 × 10−7 and P = 1.05 × 10−6, respectively). Furthermore, the A allele of rs3468 was correlated with European League Against Rheumatism nonresponse in the discovery cohort ( P = 0.03; n = 56) and in the independent replication cohort ( P = 0.003; n = 1,204). Conclusion We identify DNA methylation as a potential biomarker of response to TNFi therapy, and we report the association between response and the LRPAP1 gene, which encodes a chaperone of low-density lipoprotein receptor-related protein 1. Additional replication experiments in independent sample collections are now needed. [ABSTRACT FROM AUTHOR]

Workplace deviant behavior has traditionally been studied with respect to business or for-profit organizations. In this article, we argue that nonprofit organizations also experience deviance, and due to their unique characteristics, they deserve special attention for extending the understanding of workplace deviant behavior to other types of organizations. Based on a review of the literature on deviance, we develop a general model of workplace deviance that we apply to nonprofit organizations. Based on the integrative conceptual framework, we advance relevant propositions for understanding and explaining deviance in nonprofit organizations. [ABSTRACT FROM AUTHOR]