Jennifer Mp Woo

Association of IRF5 polymorphisms with activation of the interferon α pathway

Objective The genetic association of interferon regulatory factor 5 (IRF5) with systemic lupus erythematosus (SLE) susceptibility has been convincingly established. To gain understanding of the effect of IRF5 variation in individuals without SLE, a study was undertaken to examine whether such genetic variation predisposes to activation of the interferon α (IFNα) pathway. Methods Using a computer simulated approach, 14 single nucleotide polymorphisms (SNPs) and haplotypes of IRF5 were tested for association with mRNA expression levels of IRF5, IFNα and IFN-inducible genes and chemokines in lymphoblastoid cell lines (LCLs) from individuals of European (CEU), Han Chinese (CHB), Japanese (JPT) and Yoruba Nigerian (YRI) backgrounds. IFN-inducible gene expression was assessed in LCLs from children with SLE in the presence and absence of IFNα stimulation. Results The major alleles of IRF5 rs13242262 and rs2280714 were associated with increased IRF5 mRNA expression levels in the CEU, CHB+JPT and YRI samples. The minor allele of IRF5 rs10488631 was associated with increased IRF5, IFNα and IFN-inducible chemokine expression in CEU (pc=0.0005, 0.01 and 0.04, respectively). A haplotype containing these risk alleles of rs13242262, rs10488631 and rs2280714 was associated with increased IRF5, IFNα and IFN-inducible chemokine expression in CEU LCLs. In vitro studies showed specific activation of IFN-inducible genes in LCLs by IFNα. Conclusions SNPs of IRF5 in healthy individuals of a number of ethnic groups were associated with increased mRNA expression of IRF5. In European-derived individuals, an IRF5 haplotype was associated with increased IRF5, IFNα and IFN-inducible chemokine expression. Identifying individuals genetically predisposed to increased IFN-inducible gene and chemokine expression may allow early detection of risk for SLE.

Treatment with apolipoprotein A-1 mimetic peptide reduces lupus-like manifestations in a murine lupus model of accelerated atherosclerosis

IntroductionThe purpose of this study was to evaluate the effects of L-4F, an apolipoprotein A-1 mimetic peptide, alone or with pravastatin, in apoE-/-Fas-/-C57BL/6 mice that spontaneously develop immunoglobulin G (IgG) autoantibodies, glomerulonephritis, osteopenia, and atherosclerotic lesions on a normal chow diet.MethodsFemale mice, starting at eight to nine weeks of age, were treated for 27 weeks with 1) pravastatin, 2) L-4F, 3) L-4F plus pravastatin, or 4) vehicle control, followed by disease phenotype assessment.ResultsIn preliminary studies, dysfunctional, proinflammatory high-density lipoproteins (piHDL) were decreased six hours after a single L-4F, but not scrambled L-4F, injection in eight- to nine-week old mice. After 35 weeks, L-4F-treated mice, in the absence/presence of pravastatin, had significantly smaller lymph nodes and glomerular tufts (PL, LP< 0.05), lower serum levels of IgG antibodies to double stranded DNA (dsDNA) (PL< 0.05) and oxidized phospholipids (oxPLs) (PL, LP< 0.005), and elevated total and vertebral bone mineral density (PL, LP< 0.01) compared to vehicle controls. Although all treatment groups presented larger aortic root lesions compared to vehicle controls, enlarged atheromas in combination treatment mice had significantly less infiltrated CD68+ macrophages (PLP< 0.01), significantly increased mean α-actin stained area (PLP< 0.05), and significantly lower levels of circulating markers for atherosclerosis progression, CCL19 (PL, LP< 0.0005) and VCAM-1 (PL< 0.0002).ConclusionsL-4F treatment, alone or with pravastatin, significantly reduced IgG anti-dsDNA and IgG anti-oxPLs, proteinuria, glomerulonephritis, and osteopenia in a murine lupus model of accelerated atherosclerosis. Despite enlarged aortic lesions, increased smooth muscle content, decreased macrophage infiltration, and decreased pro-atherogenic chemokines in L-4F plus pravastatin treated mice suggest protective mechanisms not only on lupus-like disease, but also on potential plaque remodeling in a murine model of systemic lupus erythematosus (SLE) and accelerated atherosclerosis.

Plasma levels of osteopontin identify patients at risk for organ damage in systemic lupus erythematosus

IntroductionOsteopontin (OPN) has been implicated as a mediator of Th17 regulation via type I interferon (IFN) receptor signaling and in macrophage activity at sites of tissue repair. This study assessed whether increased circulating plasma OPN (cOPN) precedes development of organ damage in pediatric systemic lupus erythematosus (pSLE) and compared it to circulating plasma neutrophil gelatinase-associated lipocalin (cNGAL), a predictor of increased SLE disease activity.MethodscOPN and cNGAL were measured in prospectively followed pSLE (n = 42) and adult SLE (aSLE; n = 23) patients and age-matched controls. Time-adjusted cumulative disease activity and disease damage were respectively assessed using adjusted-mean SLE disease activity index (SLEDAI) (AMS) and SLICC/ACR damage index (SDI).ResultsCompared to controls, elevated cOPN and cNGAL were observed in pSLE and aSLE. cNGAL preceded worsening SLEDAI by 3-6 months (P = 0.04), but was not associated with increased 6-month AMS. High baseline cOPN, which was associated with high IFNalpha activity and expression of autoantibodies to nucleic acids, positively correlated with 6-month AMS (r = 0.51 and 0.52, P = 0.001 and 0.01 in pSLE and aSLE, respectively) and was associated with SDI increase at 12 months in pSLE (P = 0.001). Risk factors for change in SDI in pSLE were cOPN (OR 7.5, 95% CI [2.9-20], P = 0.03), but not cNGAL, cumulative prednisone, disease duration, immunosuppression use, gender or ancestry using univariate and multivariate logistic regression. The area under the curve (AUC) when generating the receiver-operating characteristic (ROC) of baseline cOPN sensitivity and specificity for the indication of SLE patients with an increase of SDI over a 12 month period is 0.543 (95% CI 0.347-0.738; positive predictive value 95% and negative predictive value 38%).ConclusionHigh circulating OPN levels preceded increased cumulative disease activity and organ damage in SLE patients, especially in pSLE, and its value as a predictor of poor outcome should be further validated in large longitudinal cohorts.

Efficacy and safety of biological agents for systemic juvenile idiopathic arthritis: a systematic review and meta-analysis of randomized trials

OBJECTIVE To define the optimal biologic agent for systemic JIA (sJIA) based on safety and efficacy data from a randomized controlled trial (RCT). METHODS Through a systematic literature search, sJIA RCTs evaluating biologic agents were identified. The primary efficacy outcome was defined as a 30% improvement according to the modified American College of Rheumatology Paediatric 30 response criteria (JIA ACR30). The primary safety outcome was defined as serious adverse events (SAEs). Outcomes were analysed by pairwise and network meta-analyses. The quality of evidence between biologic agents was assessed by applying the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology. RESULTS From the 493 citations originally identified, 5 RCTs were eligible for inclusion-one each for anakinra, canakinumab and tocilizumab and two for rilonacept: all vs placebo. While all were effective, the network meta-analysis indicated with low-quality evidence (due to indirect comparison and inconsistency) that rilonacept-treated patients were less likely to respond than those treated with canakinumab [odds ratio (OR) 0.10 (95% CI 0.02, 0.38), P = 0.001] or tocilizumab [OR 0.12 (95% CI 0.03, 0.44), P = 0.001]. Risks of SAEs were similar among the biologic agents (supported by very low-quality evidence) and not different from placebo. CONCLUSION Despite heterogeneous eligibility criteria and study designs across the five studies and different modified JIA ACR30 criteria, this meta-analysis of short-term RCTs presents empirical evidence that canakinumab and tocilizumab are more effective than rilonacept. Biologic agents in sJIA seem safe and comparable with respect to SAE risk in the short term.

Publication Outcomes of Abstracts Presented at an American College of Rheumatology/Association of Rheumatology Health Professionals Annual Scientific Meeting

The American College of Rheumatology (ACR) and the Association of Rheumatology Health Professionals (ARHP) Annual Scientific Meeting is an important forum for early dissemination of novel ideas. However, unlike published studies in peer‐reviewed journals, reviewers select abstracts based solely on a general summary of the research. Analyses of the scientific impact and the publication record of the ACR/ARHP Annual Meeting have not been previously described. This study characterizes publication trends and outcomes associated with abstracts presented at the ACR/ARHP Annual Scientific Meeting.

Biological agents in polyarticular juvenile idiopathic arthritis: A meta-analysis of randomized withdrawal trials ☆ ☆☆

BACKGROUND AND OBJECTIVE Although various biological agents are in use for polyarticular juvenile idiopathic arthritis (pJIA), head-to-head trials comparing the efficacy and safety among them are lacking. We aimed to compare the efficacy and safety of biological agents in pJIA using all currently available randomized withdrawal trials (wRCTs). METHODS A systematic search of MEDLINE, EMBASE, CENTRAL, and clinicaltrials.gov was performed. Eligible wRCTs: patients with pJIA where a biological agent was compared with another biological agent or placebo. Efficacy was evaluated using disease flare as a measure. Adverse events (AEs) and serious AEs were evaluated. Network meta-analysis compared biological agents based on a (empirical Bayes) mixed-effects logistic regression model that combines statistical inference from both direct and indirect comparisons of the treatment effects between biological agents. RESULTS Of 496 references identified, five wRCTs were included-abatacept, adalimumab, anakinra, etanercept, and tocilizumab, one trial each, all vs. placebo. There were no differences in efficacy among biological agents and most showed statistically significant efficacy compared with placebo (nearly all exceptions were in agreement with the original study data). Serious AEs occurred very infrequently (0-8%) and an analysis was not possible. There were no differences for AEs when compared among biological agents or to placebo. CONCLUSION There were no statistical differences among biological agents for efficacy or safety. Overall, biological agents were effective and safe when compared to placebo. Based on these data, other considerations such as price and availability may need to be used to decide among biological agents when treating pJIA patients.

46-Year Trends in Systemic Lupus Erythematosus Mortality in the United States, 1968 to 2013: A Nationwide Population-Based Study

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with limited treatment options (1). Five- and 10-year survival rates for patients with SLE improved from less than 50% in the 1950s to more than 90% in the 1980s (2). However, the influence of more recent diagnostic and therapeutic developments on SLE mortality in the general population of the United States is unknown. Previous studies of SLE mortality were based primarily on deaths in patient cohorts (36), which do not capture changes in SLE incidence over time and do not reflect the true burden and trends of SLE mortality in the general population. Several studies have used population-based designs but were limited to specific regions and small samples (710). Some studies pooled deaths from multiple years (for example, 9 to 30 years) (3, 7, 10), which obscures changes in SLE mortality trends during the collection periods. These limitations may have contributed to the inconsistency of findings from previous studies (5, 6). We therefore undertook a population-based study of temporal trends and demographic and regional differences in SLE mortality in the United States from 1968 through 2013. We examined SLE mortality trends by sex, race/ethnicity, and geographic region and conducted multiple logistic regression analysis to assess the independent association of these variables with SLE mortality. Supplement. Original Version (PDF) Methods Data Sources The Centers for Disease Control and Prevention (CDC)s National Vital Statistics System maintains a mortality database, with data provided by various jurisdictions that are legally responsible for the registration of vital events and information extracted from death certificates. This database encompasses more than 99% of deaths of U.S. residents in all 50 states and the District of Columbia. Using the CDCs WONDER (Wide-ranging Online Data for Epidemiologic Research) database, we gathered data on SLE deaths from 1968 (the earliest year for which the CDC published county-level mortality data) through 2013 (11). Death certificates in the United States provide the International Classification of Diseases (ICD) code for the underlying cause of death, which is defined as the disease or injury that initiated the events resulting in death (12). Deaths were attributed to SLE if an ICD code for SLE was listed as the underlying cause on the death certificate (Appendix Table 1). Age, race/ethnicity, and geographic region were ascertained using standard methods (13). Since 1999, race has been classified as white, black or African American, Asian or Pacific Islander (PI), or American Indian (AI) or Alaska Native (AN). Before 1999, AI, AN, Asian, and PI were grouped into an other race category. Ethnicity is classified as Hispanic or non-Hispanic, with this information available only after 1999. Geographic region is classified according to U.S. census regional divisions (Appendix Table 2). Appendix Table 1. ICD Codes for SLE Appendix Table 2. Census Regions We used the CDC WONDER database to obtain annual death counts in the entire U.S. population and separately by sex, race/ethnicity, and U.S. geographic region (Northeast, Midwest, South, or West). Counts of SLE deaths for smaller racial groups (Asian, PI, AI, and AN) were collapsed due to aggregated reporting by the CDC to avoid potential threats to confidentiality associated with counts at higher resolutions. Because information on ethnicity was not collected before 1999, we used 2 alternate racial/ethnic classifications. For analyses that included deaths before 1999, we used 3 race categories (white, black, and Asian/PI/AI/AN), and for analyses limited to 1999 through 2013, we used 4 racial/ethnic categories (non-Hispanic white, non-Hispanic black, Hispanic, and Asian/PI/AI/AN). For data from 1999 through 2013, we also obtained death counts for 192 combinations of sex, race/ethnicity, region, and age (64 or 65 years), pooled across multiple years (into 3 periods) for confidentiality. For calculation of mortality rates, the size of the population (total and each group) was obtained from the U.S. Census Bureau files for each year. Annual Mortality Rates We quantified age-specific crude mortality rates for SLE and non-SLE causes for each year from 1968 through 2013 as the number of deaths divided by the number of persons in the U.S. general population. This was done within age strata (10-year ranges, except at the extremes of the age distribution, as shown in Appendix Table 3) for the total U.S. population and separately for each sex, race, and geographic region. Appendix Table 3. Example of Direct Age Standardization Calculation: SLE Mortality in the U.S. Female Population for 2013* To calculate the overall age-standardized mortality rate (ASMR) for the population for each year from 1968 through 2013, we combined the yearly age-specific crude mortality rates with the age distribution of the U.S. population in 2000, as described in Appendix Table 3. This was done separately for the total U.S. population and for each sex, race, and geographic region and for both SLE deaths and non-SLE deaths. We then computed the ratio of the SLE ASMR to the non-SLE ASMR for each year. Statistical Analysis We used joinpoint regression to fit piecewise-linear (or broken-line) trends to the yearly SLE ASMR, the yearly non-SLE ASMR, and the ratio of the former to the latter over the 46-year period. Joinpoint regression identifies a set of joinpoints (or knots)the time points (calendar years) at which the change in the slope of the ASMR is statistically significantand computes the slope (year-to-year percentage change in annual ASMR) and the 95% CI over each linear trend segment between adjacent joinpoints (14). This approach identifies the year when the trend (slope of the increase or decrease) in mortality rate changes significantly and determines the magnitude of the change. Joinpoint regression analyses were conducted using the National Cancer Institute Joinpoint Regression Program, which uses a grid search method (15) to find the best locations for the joinpoints based on a least-squares fit of the data and uses a permutation test to determine the optimal number of joinpoints (16) (Appendix). A second set of analyses was designed to determine the independent relationship of age (64 vs. 65 years), sex, race/ethnicity, geographic region, and calendar year with SLE mortality. Data were pooled across calendar years into three 5-year periods for this analysis (to allow downloading of death counts without a threat to confidentiality): 1999 through 2003, 2004 through 2008, and 2009 through 2013. We performed multiple logistic regression on the aggregated group-level data (SLE death count and population size for 192 groups defined by 2 age categories, 2 sexes, 4 race/ethnicity categories, and 4 geographic regions, summed over all calendar years in each of the 3 periods) using maximum likelihood estimation with frequency weights (logistic command using the fweight option in Stata, version 13.1 [StataCorp]). Frequency weights represented total SLE deaths or the total population without SLE deaths for each group in each period. In addition to the main effects for each of the demographic, geographic, and time variables, we tested for effect modification by including the pairwise interaction terms of race/ethnicity, sex, geographic location, and calendar year in the model. For interactions that were statistically significant (2-sided P< 0.05), we assessed SLE mortality associations stratified by race/ethnicity. We estimated the odds ratio and 95% CI. We then used the Stata margins command to calculate model-predicted annual mortality for the individual demographic, region, or time characteristics integrated across all other characteristics and the pwcompare option to compute the differences in predicted annual mortality between 2 strata (for example, old vs. young or male vs. female), integrated across all other demographic, region, and time variables. Sensitivity Analysis Since 1999, information on the contributing cause of death, which is defined as other significant conditions contributing to death but not resulting in the underlying cause, has been available in the CDC WONDER database. To address the possibility that SLE may not be listed as the underlying cause on death certificates of some patients who died of SLE complications and that this coding error may differ across different subpopulations, we performed the multiple logistic regression analyses for cases where SLE was listed as a contributing cause of death. Role of the Funding Source The funding agencies had no role in this study. Results We identified 50249 deaths with SLE listed as the underlying cause in the United States from 1968 through 2013. The proportions of SLE deaths among females, nonwhite persons, and residents of the South and West were higher than the proportions of non-SLE deaths (Table 1). Table 1. Demographic Characteristics of SLE and Non-SLE Deaths, 19682013* Mortality Trends Overall and by Sex, Race, and Geographic Region The ASMR for SLE decreased from 0.45 (95% CI, 0.42 to 0.48) per 100000 persons in 1968 to 0.34 (CI, 0.32 to 0.36) per 100000 persons in 2013. However, the relative decrease in the SLE ASMR (24.4%) was lower than that for non-SLE causes (43.9%) during the same period (Table 2). Table 2. Cumulative Percentage Change in SLE ASMR, Non-SLE ASMR, and Ratio of SLE to Non-SLE ASMR, 19682013 The SLE ASMR was lower in 2013 than in 1968 among males and females, among white persons and black persons, and in all geographic regions (Table 2), but the relative cumulative decrease in the SLE ASMR was smaller in females than in males, in black persons than in white persons, and in the South than in other geographic regions. The decrease in the SLE ASMR was smaller than the decrease in the non-SLE ASMR in all subpopulations except in males, where the cumulative change between 1968 and 2013 was similar for

CD3Z hypermethylation is associated with severe clinical manifestations in systemic lupus erythematosus and reduces CD3ζ-chain expression in T cells

Objective. The importance of hypomethylation in SLE is well recognized; however, the significance of hypermethylation has not been well characterized. We screened hypermethylated marks in SLE and investigated their possible implications. Methods. DNA methylation marks were screened in SLE whole-blood DNA by microarray, and two marks (CD3Z and VHL hypermethylations) were confirmed by a methylation single-base extension method in two independent ethnic cohorts consisting of 207 SLE patients and 151 controls. The correlation with clinical manifestations and the genetic influence on those epigenetic marks were analysed. Results. Two epigenetic marks, CD3Z and VHL hypermethylation, were significantly correlated with SLE: CD3Z hypermethylation (odds ratio = 7.76; P = 1.71 × 10−13) and VHL hypermethylation (odds ratio = 3.77; P = 3.20 × 10−8), and the increased CD3Z methylation was correlated with downregulation of the CD3&zgr;-chain in SLE T cells. In addition, less genetic influence on CD3Z methylation relative to VHL methylation was found in analyses of longitudinal and twin samples. Furthermore, a higher CD3Z methylation level was significantly correlated with a higher SLE disease activity index and more severe clinical manifestations, such as proteinuria, haemolytic anaemia and thrombocytopenia, whereas VHL hypermethylation was not. Conclusion. CD3Z hypermethylation is an SLE risk factor that can be modified by environmental factors and is associated with more severe SLE clinical manifestations, which are related to deranged T cell function by downregulating the CD3&zgr;-chain.

A structural rationale for SV40 Vp1 temperature-sensitive mutants and their complementation

Two groups of temperature‐sensitive (ts) mutants, termed ts B and ts C, have mutations in the major capsid protein of SV40, Vp1. These mutants have virion assembly defects at the nonpermissive temperature, but can complement one another when two mutants, one from each group, coinfect a cell. A third group of mutants, termed ts BC, have related phenotypes, but do not complement other mutants. We found that the mutations fall into two structural and functional classes. All ts C and one ts BC mutations map to the region close to the Ca2+ binding sites, and are predicted to disrupt the insertion of the distal part of the C‐terminal invading arm (C‐arm) into the receiving clamp. They share a severe defect in assembly at the nonpermissive temperature, with few capsid proteins attached to the viral minichromosome. By contrast, all ts B and most ts BC mutations map to a contiguous region including acceptor sites for the proximal part of the C‐arm and intrapentamer contacts. These mutants form assembly intermediates that carry substantial capsid proteins on the minichromosome. Thus, accurate virion assembly is prevented by mutations that disrupt interactions between the receiving pentamer and both the proximal and distal parts of the C‐arms, with the latter having a greater effect. The distinct spatial localization and assembly defects of the two classes of mutants provide a rationale for their intracistronic complementation and suggest models of capsid assembly.

Folate usage in MTX-treated juvenile idiopathic arthritis (JIA) patients is inconsistent and highly variable

Folate supplementation is widely accepted and utilized for the prevention of adverse events in juvenile idiopathic arthritis (JIA) patients who are treated with methotrexate. Despite the widespread use of folate supplementation, there is a lack of convincing evidence to support the role of folate in the enhancement of methotrexate efficacy and the prevention of methotrexate-related adverse events. In order to understand current practices used by experts, we surveyed 214 pediatric rheumatologists around the globe. Seventy-one unique folate supplementation regimens were reported for this study. Results indicated that folate supplementation (either in the form of folic acid or folinic acid) is inconsistent and highly variable within the United States as well as between the United States and other countries. This level of variability is often associated with lack of evidence and emphasizes the need for well-designed clinical trials to support a rational folate supplementation regimen in patients with JIA who are treated with methotrexate.