Genetic analysis of juvenile rheumatoid arthritis: approaches to complex traits

Adherence to exercise therapy among children and adolescents with Juvenile idiopathic arthritis: a scoping review

PURPOSE

To identify parameters and measurement methods of exercise therapy adherence, as well as barriers and facilitators affecting adherence among children and adolescents with juvenile idiopathic arthritis (JIA).

METHODS

Studies were eligible for inclusion if patients were 0-18 years of age, had JIA, and the focus of the research was on exercise therapy patterns, measurement/parameters of exercise adherence, and barriers/facilitators for exercise adherence. Two reviewers independently identified and categorized the barriers and facilitators to exercise therapy adherence using the International Classification of Functioning, Disability, and Health (ICF).

RESULTS

Twenty articles were included in this review. Among patients with JIA, 29%-99% adhered to exercise therapy. The most commonly measured parameters of adherence were session completion and behavior component, with a self-report log serving as the most common means of assessment. Time pressure, symptoms related to JIA, lack of enjoyment, and insufficient motivation were the main barriers. Facilitators were commonly identified as adequate motivation, effective symptoms management, and social support.

CONCLUSIONS

Future interventions should consider the identified factors to promote exercise engagement in children and adolescents with JIA. Strategies for promoting exercise adherence in children and adolescents with JIA is needed.

Genetic Background and Molecular Mechanisms of Juvenile Idiopathic Arthritis

Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease in the paediatric population. JIA comprises a heterogeneous group of disorders with different onset patterns and clinical presentations with the only element in common being chronic joint inflammation. This review sought to evaluate the most relevant and up-to-date evidence on current knowledge regarding the pathogenesis of JIA subtypes to provide a better understanding of these disorders. Despite significant improvements over the past decade, the aetiology and molecular mechanisms of JIA remain unclear. It has been suggested that the immunopathogenesis is characterised by complex interactions between genetic background and environmental factors that may differ between JIA subtypes. Human leukocyte antigen (HLA) haplotypes and non-HLA genes play a crucial role in the abnormal activation of both innate and adaptive immune cells that cooperate in causing the inflammatory process. This results in the involvement of proinflammatory cytokines, including tumour necrosis factor (TNF)α, interleukin (IL)-1, IL-6, IL-10, IL-17, IL-21, IL-23, and others. These mediators, interacting with the surrounding tissue, cause cartilage stress and bone damage, including irreversible erosions. The purpose of this review is to provide a comprehensive overview of the genetic background and molecular mechanisms of JIA.

Genetic architecture study of rheumatoid arthritis and juvenile idiopathic arthritis

BACKGROUND

Rheumatoid arthritis and juvenile idiopathic arthritis are two types of autoimmune diseases with inflammation at the joints, occurring to adults and children respectively. There are phenotypic overlaps between these two types of diseases, despite the age difference in patient groups.

METHODS

To systematically compare the genetic architecture of them, we conducted analyses at gene and pathway levels and constructed protein-protein-interaction network based on summary statistics of genome-wide association studies of these two diseases. We examined their difference and similarity at each level.

RESULTS

We observed extensive overlap in significant SNPs and genes at the human leukocyte antigen region. In addition, several SNPs in other regions of the human genome were also significantly associated with both diseases. We found significantly associated genes enriched in 32 pathways shared by both diseases. Excluding genes in the human leukocyte antigen region, significant enrichment is present for pathways like interleukin-27 pathway and NO2-dependent interleukin-12 pathway in natural killer cells.

DISCUSSION

The identification of commonly associated genes and pathways may help in finding population at risk for both diseases, as well as shed light on repositioning and designing drugs for both diseases.

Measuring consistency among gene set analysis methods: A systematic study

Gene set analysis is a quantitative approach for generating biological insight from gene expression datasets. The abundance of gene set analysis methods speaks to their popularity, but raises the question of the extent to which results are affected by the choice of method. Our systematic analysis of 13 popular methods using 6 different datasets, from both DNA microarray and RNA-Seq origin, shows that this choice matters a great deal. We observed that the overall number of gene sets reported by each method differed by up to 2 orders of magnitude, and there was a bias toward reporting large gene sets with some methods. Furthermore, there was substantial disagreement between the 20 most statistically significant gene sets reported by the methods. This was also observed when expanding to the 100 most statistically significant reported gene sets. For different datasets of the same phenotype/condition, the top 20 and top 100 most significant results also showed little to no agreement even when using the same method. GAGE, PAGE, and ORA were the only methods able to achieve relatively high reproducibility when comparing the 20 and 100 most statistically significant gene sets. Biological validation on a juvenile idiopathic arthritis (JIA) dataset showed wide variation in terms of the relevance of the top 20 and top 100 most significant gene sets to known biology of the disease, where GAGE predicted the most relevant gene sets, followed by GSEA, ORA, and PAGE.

Comorbidity of Type 1 Diabetes Mellitus in Patients with Juvenile Idiopathic Arthritis

OBJECTIVES

To determine the prevalence of type 1 diabetes mellitus (T1D) in patients with juvenile idiopathic arthritis (JIA) and to characterize patients having both.

STUDY DESIGN

Diabetes comorbidity was recorded in the National Pediatric Rheumatologic Database since 2012. Data from the North Rhine-Westphalian diabetes registry served as the reference population for the prevalence of diabetes in the general population. The National Pediatric Rheumatologic Database data were indirectly standardized for age and sex for comparison with the general population. The diabetes prevalence ratio was calculated using the Poisson regression model.

RESULTS

The analysis included 12 269 patients with JIA. A total of 58 patients had comorbid T1D, and the diabetes prevalence was 0.5%. The mean age was 11.6 years at the time of documentation, and the mean disease duration was 4.2 years. Compared with the general population, the prevalence of diabetes in patients with JIA was significantly increased (prevalence ratio 1.76 [95% CI 1.34; 2.28], P < .001). The onset of diabetes in patients with JIA was earlier than that reported in the reference data. Sixty-three percent of patients developed T1D before JIA. On average, diabetes onset was 56 months before the onset of JIA. Patients who first developed JIA developed T1D on average 40 months later. The majority of patients had not received disease-modifying antirheumatic drugs before diabetes onset.

CONCLUSIONS

T1D occurs more frequently in patients with JIA than in the general population. The likelihood of T1D occurrence appears to be slightly higher before JIA manifestation and without disease-modifying antirheumatic drug therapy after JIA onset.

The DNA methylation landscape of CD4+ T cells in oligoarticular juvenile idiopathic arthritis

Juvenile idiopathic arthritis (JIA) is presumed to be driven by an adverse combination of genes and environment. Epigenetic processes, including DNA methylation, act as a conduit through which the environment can regulate gene activity. Altered DNA methylation has been associated with adult autoimmune rheumatic diseases such as rheumatoid arthritis, but studies are lacking for paediatric autoimmune rheumatic diseases including JIA. Here, we performed a genome-scale case-control analysis of CD4⁺ T cell DNA methylation from 56 oligoarticular JIA (oJIA) cases and 57 age and sex matched controls using Illumina HumanMethylation450 arrays. DNA methylation at each array probe was tested for association with oJIA using RUV (Remove Unwanted Variation) together with a moderated t-test. Further to this 'all-inclusive' analysis, we stratified by age at diagnosis (≤6yrs, >6yrs) and by sex as potential sources of heterogeneity. Following False Discovery Rate (FDR) adjustment, no probes were associated with oJIA in the all-inclusive, >6yrs-diagnosed, or sex-stratified analyses, and only one probe was associated with oJIA in the ≤6yrs-diagnosed analysis. We attempted technical validation and replication of 14 probes (p_unadj<0.01) at genes of known/potential relevance to disease. At VPS53, we demonstrated a regional shift towards higher methylation in oJIA (all-inclusive) compared to controls. At REEP3, where polymorphism has been previously associated with JIA, we demonstrated higher DNA methylation in male oJIA compared to male controls. This is the most comprehensive JIA case-control analysis of DNA methylation to date. While we have generated some evidence of altered methylation in oJIA, substantial differences are not apparent in CD4⁺ T cells. This may indicate a lesser relevance of DNA methylation levels in childhood, compared to adult, rheumatic disease.

Genetic insights into juvenile idiopathic arthritis derived from deep whole genome sequencing

Deep whole genome sequencing (WGS) allows for the comprehensive study of genetic landscapes at finer resolution than array based methods. We conducted deep WGS on children with the polyarticular form of juvenile idiopathic arthritis (JIA), using 2 independent cohorts to ascertain the sequencing fidelity. Genome wide SNP density analysis identified 18 SNP hotspots with comparison to the 1000 Genome Projects (1KGP) data. A subset of the genes adjacent to SNP hotspots showed statistically significant enrichment in immunological processes. Genes adjacent to indel hotspots were functionally related to G-protein coupled signaling pathways. Further analyses elucidated significantly more JIA SNPs with regulatory potential compared to 1KGP data. Furthermore, SNPs located within linkage disequibilium (LD) blocks containing previously identified JIA-associated SNPs demonstrated higher regulation potential compared to SNPs outside LD blocks. We also demonstrated enrichment of novel JIA variants in histone modification peaks and DNase hypersensitivity sites in B cells. This study greatly expands the number of genetic variants that may contribute to JIA and give us some clues into what may trigger this disease. To date, this study is the first deep WGS effort on children with JIA and provides useful genetic resources for research communities particularly in understanding JIA etiology.

Juvenile idiopathic arthritis: what is the utility of ultrasound?

Juvenile idiopathic arthritis (JIA) is a heterogeneous condition and an important cause of acquired disability in children. Evidence supports early treatment to prevent future complications. This relies on prompt diagnosis, achieved by a high index of clinical suspicion and supportive evidence, including the detection of joint and or tendon inflammation. Ultrasound is a readily accessible, well-tolerated, safe and accurate modality for assessing joints and the surrounding soft tissues. It can also be used to guide therapy into those joints and tendon sheaths resistant to systemic treatments. Ultrasound imaging is highly operator dependent, and the developing skeleton poses unique challenges in interpretation with sonographic findings that can mimic pathology and vice versa. Ultrasound technology has been rapidly improving and is more accessible than ever before. In this article, we review the normal appearances, highlight potential pitfalls and present the key pathological findings commonly seen in JIA.

TNF-α Polymorphisms in Juvenile Idiopathic Arthritis: Which Potential Clinical Implications?

Whether tumor necrosis factor alpha (TNF-α) gene polymorphisms (SNPs) influence disease susceptibility and treatment of patients with juvenile idiopathic arthritis (JIA) is presently uncertain. TNF-α is one of the most important cytokine involved in JIA pathogenesis. Several single nucleotide polymorphisms (SNPs) have been identified within the region of the TNF-α gene but only a very small minority have proven functional consequences and have been associated with susceptibility to JIA. An association between some TNF-α SNPs and adult rheumatoid arthritis (RA) susceptibility, severity and clinical response to anti-TNF-α treatment has been reported. The most frenquetly studied TNF-α SNP is located at -308 position, where a substitution of the G allele with the rare A allele has been found. The presence of the allele -308A is associated to JIA and to a poor prognosis. Besides, the -308G genotype has been associated with a better response to anti-TNF-α therapy in JIA patients, confirming adult data. Psoriatic and oligoarticular arthritis are significantly associated to the -238 SNP only in some works. Studies considering other SNPs are conflicting and inconclusive. Large scale studies are required to define the contribution of TNF-α gene products to disease pathogenesis and anti-TNF-α therapeutic efficacy in JIA.

A comprehensive review of the genetics of juvenile idiopathic arthritis

Juvenile idiopathic arthritis (JIA) is the most common chronic arthropathy of childhood which is believed to be influenced by both genetic and environmental factors. The progress in identifying genes underlying JIA susceptibility using candidate gene association studies has been slow. Several associations between JIA and variants in the genes encoding the human leukocyte antigens (HLA) have been confirmed and replicated in independent cohorts. However it is clear that genetic variants outside the HLA also influence susceptibility to JIA. While a large number of non-HLA candidate genes have been tested for associations, only a handful of reported associations such as PTPN22 have been validated. In this review we discuss the principles behind genetic studies of complex traits like JIA, and comprehensively catalogue non-HLA candidate-gene association studies performed in JIA to date and review several validated associations. Most candidate gene studies are underpowered and do not detect associations, and those that do are often not replicated. We also discuss the principles behind genome-wide association studies and discuss possible implications for identifying genes underlying JIA. Finally we discuss several genetic variants underlying multiple clinically distinct autoimmune phenotypes.