Patient-Reported Outcomes (PROs) and PRO Remission Rates in 12,262 Biologic-Naïve Patients With Psoriatic Arthritis Treated With Tumor Necrosis Factor Inhibitors in Routine Care.

OBJECTIVE: To evaluate patient-reported outcomes (PROs) after initiation of tumor necrosis factor inhibitor (TNFi) treatment in European real-world patients with psoriatic arthritis (PsA). Further, to investigate PRO remission rates across treatment courses, registries, disease duration, sex, and age at disease onset. METHODS: Visual analog scale or numerical rating scale scores for pain, fatigue, patient global assessment (PtGA), and the Health Assessment Questionnaire-Disability Index (HAQ-DI) from 12,262 patients with PsA initiating a TNFi in 13 registries were pooled. PRO remission rates (pain ≤ 1, fatigue ≤ 2, PtGA ≤ 2, and HAQ-DI ≤ 0.5) were calculated for patients still on the treatment. RESULTS: For the first TNFi, median pain score was reduced by approximately 50%, from 6 to 3, 3, and 2; as were fatigue scores, from 6 to 4, 4, and 3; PtGA scores, from 6 to 3, 3, and 2; and HAQ-DI scores, from 0.9 to 0.5, 0.5, and 0.4 at baseline, 6, 12, and 24 months, respectively. Six-month Lund Efficacy Index (LUNDEX)-adjusted remission rates for pain, fatigue, PtGA, and HAQ-DI scores were 24%, 31%, 36%, and 43% (first TNFi); 14%, 19%, 23%, and 29% (second TNFi); and 9%, 14%, 17%, and 20% (third TNFi), respectively. For biologic-naïve patients with disease duration < 5 years, 6-month LUNDEX-adjusted remission rates for pain, fatigue, PtGA, and HAQ-DI scores were 22%, 28%, 33%, and 42%, respectively. Corresponding rates for patients with disease duration > 10 years were 27%, 32%, 41%, and 43%, respectively. Remission rates were 33%, 40%, 45%, and 56% for men and 17%, 23%, 24%, and 32% for women, respectively. For patients aged < 45 years at diagnosis, 6-month LUNDEX-adjusted remission rate for pain was 29% vs 18% for patients ≥ 45 years. CONCLUSION: In 12,262 biologic-naïve patients with PsA, 6 months of treatment with a TNFi reduced pain by approximately 50%. Marked differences in PRO remission rates across treatment courses, registries, disease duration, sex, and age at onset of disease were observed, emphasizing the potential influence of factors other than disease activity on PROs.

Commonalities and differences in set-up and data collection across European spondyloarthritis registries - results from the EuroSpA collaboration.

BACKGROUND: In European axial spondyloarthritis (axSpA) and psoriatic arthritis (PsA) clinical registries, we aimed to investigate commonalities and differences in (1) set-up, clinical data collection; (2) data availability and completeness; and (3) wording, recall period, and scale used for selected patient-reported outcome measures (PROMs). METHODS: Data was obtained as part of the EuroSpA Research Collaboration Network and consisted of (1) an online survey and follow-up interview, (2) upload of real-world data, and (3) selected PROMs included in the online survey. RESULTS: Fifteen registries participated, contributing 33,948 patients (axSpA: 21,330 (63%), PsA: 12,618 (37%)). The reported coverage of eligible patients ranged from 0.5 to 100%. Information on age, sex, biological/targeted synthetic disease-modifying anti-rheumatic drug treatment, disease duration, and C-reactive protein was available in all registries with data completeness between 85% and 100%. All PROMs (Bath Ankylosing Spondylitis Disease Activity and Functional Indices, Health Assessment Questionnaire, and patient global, pain and fatigue assessments) were more complete after 2015 (68-86%) compared to prior (50-79%). Patient global, pain and fatigue assessments showed heterogeneity between registries in terms of wording, recall periods, and scale. CONCLUSION: Important heterogeneity in registry design and data collection across fifteen European axSpA and PsA registries was observed. Several core measures were widely available, and an increase in data completeness of PROMs in recent years was identified. This study might serve as a basis for examining how differences in data collection across registries may impact the results of collaborative research in the future.

Predictors of ASDAS-CRP inactive disease in axial spondyloarthritis during treatment with TNF-inhibitors: Data from the EuroSpA collaboration.

OBJECTIVES: In patients with axial spondyloarthritis (axSpA) initiating their first tumor necrosis factor alpha-inhibitor (TNFi), we aimed to identify common baseline predictors of Ankylosing Spondylitis Disease Activity Score (ASDAS-CRP) inactive disease (primary objective) and clinically important improvement (CII) at 6 months, and drug retention at 12-months across 15 European registries. METHODS: Baseline demographic and clinical characteristics were collected. Outcomes were investigated per registry and in pooled data using logistic regression analyses on multiply imputed data. RESULTS: The consistency of baseline predictors in individual registries justified pooling the data. In the pooled dataset (n = 21,196), the 6-month rates for ASDAS inactive disease and ASDAS CII were 26% and 51%, and the 12-month drug retention rate 65% in patients with available data (n = 9,845, n = 6,948 and n = 21,196, respectively). Nine common baseline predictors of ASDAS inactive disease, ASDAS CII and 12-month drug retention were identified, and the odds ratios (95%-confidence interval) for ASDAS inactive disease were: age, per year: 0.97 (0.97-0.98), men vs. women: 1.88 (1.60-2.22), current vs. non-smoking: 0.76 (0.63-0.91), HLA-B27 positive vs. negative: 1.51 (1.20-1.91), TNF start year 2015-2018 vs. 2009-2014: 1.24 (1.06-1.45), CRP>10 vs. ≤10 mg/l: 1.49 (1.25-1.77), one unit increase in health assessment questionnaire (HAQ): 0.77 (0.58-1.03), one-millimeter (mm) increase in Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) fatigue and spinal pain: 0.99 (0.99-1.00) and 0.99 (0.99-1.99), respectively CONCLUSION: Common baseline predictors of treatment response and adherence to TNFi could be identified across data from 15 European registries, indicating that they may be universal across different axSpA populations.

Highly accessible AU-rich regions in 3' untranslated regions are hotspots for binding of regulatory factors.

Post-transcriptional regulation is regarded as one of the major processes involved in the regulation of gene expression. It is mainly performed by RNA binding proteins and microRNAs, which target RNAs and typically affect their stability. Recent efforts from the scientific community have aimed at understanding post-transcriptional regulation at a global scale by using high-throughput sequencing techniques such as cross-linking and immunoprecipitation (CLIP), which facilitates identification of binding sites of these regulatory factors. However, the diversity in the experimental procedures and bioinformatics analyses has hindered the integration of multiple datasets and thus limited the development of an integrated view of post-transcriptional regulation. In this work, we have performed a comprehensive analysis of 107 CLIP datasets from 49 different RBPs in HEK293 cells to shed light on the complex interactions that govern post-transcriptional regulation. By developing a more stringent CLIP analysis pipeline we have discovered the existence of conserved regulatory AU-rich regions in the 3'UTRs where miRNAs and RBPs that regulate several processes such as polyadenylation or mRNA stability bind. Analogous to promoters, many factors have binding sites overlapping or in close proximity in these hotspots and hence the regulation of the mRNA may depend on their relative concentrations. This hypothesis is supported by RBP knockdown experiments that alter the relative concentration of RBPs in the cell. Upon AGO2 knockdown (KD), transcripts containing "free" target sites show increased expression levels compared to those containing target sites in hotspots, which suggests that target sites within hotspots are less available for miRNAs to bind. Interestingly, these hotspots appear enriched in genes with regulatory functions such as DNA binding and RNA binding. Taken together, our results suggest that hotspots are functional regulatory elements that define an extra layer of regulation of post-transcriptional regulatory networks.

On the accuracy of short read mapping.

The development of high-throughput sequencing technologies has revolutionized the way we study genomes and gene regulation. In a single experiment, millions of reads are produced. To gain knowledge from these experiments the first thing to be done is finding the genomic origin of the reads, i.e., mapping the reads to a reference genome. In this new situation, conventional alignment tools are obsolete, as they cannot handle this huge amount of data in a reasonable amount of time. Thus, new mapping algorithms have been developed, which are fast at the expense of a small decrease in accuracy. In this chapter we discuss the current problems in short read mapping and show that mapping reads correctly is a nontrivial task. Through simple experiments with both real and synthetic data, we demonstrate that different mappers can give different results depending on the type of data, and that a considerable fraction of uniquely mapped reads is potentially mapped to an incorrect location. Furthermore, we provide simple statistical results on the expected number of random matches in a genome (E-value) and the probability of a random match as a function of read length. Finally, we show that quality scores contain valuable information for mapping and why mapping quality should be evaluated in a probabilistic manner. In the end, we discuss the potential of improving the performance of current methods by considering these quality scores in a probabilistic mapping program.

cWords - systematic microRNA regulatory motif discovery from mRNA expression data.

BACKGROUND: Post-transcriptional regulation of gene expression by small RNAs and RNA binding proteins is of fundamental importance in development of complex organisms, and dysregulation of regulatory RNAs can influence onset, progression and potentially be target for treatment of many diseases. Post-transcriptional regulation by small RNAs is mediated through partial complementary binding to messenger RNAs leaving nucleotide signatures or motifs throughout the entire transcriptome. Computational methods for discovery and analysis of sequence motifs in high-throughput mRNA expression profiling experiments are becoming increasingly important tools for the identification of post-transcriptional regulatory motifs and the inference of the regulators and their targets. RESULTS: cWords is a method designed for regulatory motif discovery in differential case-control mRNA expression datasets. We have improved the algorithms and statistical methods of cWords, resulting in at least a factor 100 speed gain over the previous implementation. On a benchmark dataset of 19 microRNA (miRNA) perturbation experiments cWords showed equal or better performance than two comparable methods, miReduce and Sylamer. We have developed rigorous motif clustering and visualization that accompany the cWords analysis for more intuitive and effective data interpretation. To demonstrate the versatility of cWords we show that it can also be used for identification of potential siRNA off-target binding. Moreover, cWords analysis of an experiment profiling mRNAs bound by Argonaute ribonucleoprotein particles discovered endogenous miRNA binding motifs. CONCLUSIONS: cWords is an unbiased, flexible and easy-to-use tool designed for regulatory motif discovery in differential case-control mRNA expression datasets. cWords is based on rigorous statistical methods that demonstrate comparable or better performance than other existing methods. Rich visualization of results promotes intuitive and efficient interpretation of data. cWords is available as a stand-alone Open Source program at Github https://github.com/simras/cWords and as a web-service at: http://servers.binf.ku.dk/cwords/.