Investigating the viability of genetic screening/testing for RA susceptibility using combinations of five confirmed risk loci

Predicting Inflammatory Arthritis in At-Risk Persons: Development of Scores for Risk Stratification

BACKGROUND

Inflammatory arthritis (IA) is an immune-related condition defined by the presence of clinical synovitis. Its most common form is rheumatoid arthritis.

OBJECTIVE

To develop scores for predicting IA in at-risk persons using multidimensional biomarkers.

DESIGN

Prospective observational cohort study.

SETTING

Single-center, Leeds, United Kingdom.

PARTICIPANTS

Persons with new musculoskeletal symptoms, a positive test result for anticitrullinated protein antibodies, and no clinical synovitis and followed for 48 weeks or more or until IA occurred.

MEASUREMENTS

A simple score was developed using logistic regression, and a comprehensive score was developed using the least absolute shrinkage and selection operator Cox proportional hazards regression. Internal validation with bootstrapping was estimated, and a decision curve analysis was done.

RESULTS

Of 455 participants, 32.5% (148 of 455) developed IA, and 15.4% (70 of 455) developed it within 1 year. The simple score identified 249 low-risk participants with a false negative rate of 5% (and 206 high-risk participants with a false-positive rate of 72%). The comprehensive score identified 119 high-risk participants with a false-positive rate of 29% (and 336 low-risk participants with a false-negative rate of 19%); 40% of high-risk participants developed IA within 1 year and 71% within 5 years.

LIMITATIONS

External validation is required. Recruitment occurred over 13 years, with lower rates of IA in later years. There was geographic variation in laboratory testing and recruitment availability.

CONCLUSION

The simple score identified persons at low risk for IA who were less likely to need secondary care. The comprehensive score identified high-risk persons who could benefit from risk stratification and preventive measures. Both scores may be useful in clinical care and should also be useful in clinical trials.

PRIMARY FUNDING SOURCE

National Institute for Health and Care Research Leeds Biomedical Research Centre.

Menthone inhibits type-I interferon signaling by promoting Tyk2 ubiquitination to relieve local inflammation of rheumatoid arthritis

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease. RA development is mediated by the abnormal activation of multiple signaling pathways. Recent studies have revealed that type-I interferon (IFN-I) signaling plays an essential role in the occurrence and development of RA. However, how to target IFN-I signaling to develop anti-rheumatoid arthritis drugs remains largely unexplored. Here, our study showed that IFN-I signaling was over-activated in articular synovial cells from collagen II-induced arthritis (CIA) mice. Interestingly, we found that a small molecule compound, menthone, strongly inhibited the activation of the IFN-I signaling pathway. Further studies revealed that menthone promoted K48-linked polyubiquitination of Tyk2, thus lowering the protein level and stability of Tyk2. Importantly, menthone administration in the local articulus of CIA mice significantly attenuated the local inflammation in CIA mice. This study could promote our understanding of rheumatoid arthritis, and also suggests a potential strategy to develop anti-RA drugs.

Preventive Treatments for Rheumatoid Arthritis: Issues Regarding Patient Preferences

The detection of biomarkers in the preclinical phase of rheumatoid arthritis (RA) and recent therapeutic advances suggest that it may be possible to identify and treat persons at high risk and to prevent the development of RA. Several trials are ongoing to test the efficacy of a therapeutic intervention in primary prevention. This paper reviews potential populations that might be considered for preventative medication. Further, we review the medications that are being explored to treat individuals considered at high risk of developing RA. Finally, in a group of asymptomatic individuals at high risk of developing RA, we assessed which factors mattered most when considering a preventive therapeutic intervention and what type of preventive treatment would be most acceptable to them. Understanding subjects' perceptions of risks and benefits and willingness to undergo preventive therapy will be important in designing and implementing screening and preventive strategies.

A Combination of CD28 (rs1980422) and IRF5 (rs10488631) Polymorphisms Is Associated with Seropositivity in Rheumatoid Arthritis: A Case Control Study

Introduction

The aim of the study was to analyse genetic architecture of RA by utilizing multiparametric statistical methods such as linear discriminant analysis (LDA) and redundancy analysis (RDA).

Methods

A total of 1393 volunteers, 499 patients with RA and 894 healthy controls were included in the study. The presence of shared epitope (SE) in HLA-DRB1 and 11 SNPs (PTPN22 C/T (rs2476601), STAT4 G/T (rs7574865), CTLA4 A/G (rs3087243), TRAF1/C5 A/G (rs3761847), IRF5 T/C (rs10488631), TNFAIP3 C/T (rs5029937), AFF3 A/T (rs11676922), PADI4 C/T (rs2240340), CD28 T/C (rs1980422), CSK G/A (rs34933034) and FCGR3A A/C (rs396991), rheumatoid factor (RF), anti–citrullinated protein antibodies (ACPA) and clinical status was analysed using the LDA and RDA.

Results

HLA-DRB1, PTPN22, STAT4, IRF5 and PADI4 significantly discriminated between RA patients and healthy controls in LDA. The correlation between RA diagnosis and the explanatory variables in the model was 0.328 (Trace = 0.107; F = 13.715; P = 0.0002). The risk variants of IRF5 and CD28 genes were found to be common determinants for seropositivity in RDA, while positivity of RF alone was associated with the CTLA4 risk variant in heterozygous form. The correlation between serologic status and genetic determinants on the 1st ordinal axis was 0.468, and 0.145 on the 2nd one (Trace = 0.179; F = 6.135; P = 0.001). The risk alleles in AFF3 gene together with the presence of ACPA were associated with higher clinical severity of RA.

Conclusions

The association among multiple risk variants related to T cell receptor signalling with seropositivity may play an important role in distinct clinical phenotypes of RA. Our study demonstrates that multiparametric analyses represent a powerful tool for investigation of mutual relationships of potential risk factors in complex diseases such as RA.

The genetics of rheumatoid arthritis: risk and protection in different stages of the evolution of RA

There is now a general consensus that RA has a spectrum of disease stages that can begin many years before the onset of clinical symptoms. It is widely thought that understanding the complex interplay between genetics and environment, and their role in pathogenesis, is essential in gaining further insight into the mechanisms that drive disease development and progression. More than 100 genetic susceptibility loci have now been identified for RA through studies that have focused on patients with established RA compared with healthy controls. Studying the early preclinical phases of disease will provide valuable insights into the biological events that precede disease and could potentially identify biomarkers to predict disease onset and future therapeutic targets. In this review we will cover recent advances in the knowledge of genetic and environmental risk factors and speculate on how these factors may influence the transition from one stage of disease to another.

Genetics of rheumatoid arthritis: time for a change!

PURPOSE OF REVIEW

To review recent progress in the genetics of rheumatoid arthritis (RA) and discuss the implications for understanding the pathogenesis of the disease as well as clinical application.

RECENT FINDINGS

Protection against anticitrullinated protein antibody (ACPA) positive RA was shown to be associated wit DRB1*1301. Genome-wide association studies (GWASs) added about 10 new loci to the list of already more than 20 loci associated with RA, so the list is now over 30. Typing for the known risk loci is not helpful for prediction of the risk for RA. It is remarkable how few functional studies have been published.

SUMMARY

Known genetic factors explain 50-60% of the genetic variance for susceptibility to ACPA-positive and 30-50% for ACPA-negative RA. Searching for the remaining missing or hidden heritability is in all probability not going to yield much for prediction and/or targeted intervention. Therefore, I conclude that if you want to find more genes you should have a lot of patience, time and money, stop with convential GWAS and invest in large-scale sequencing of selected patients and controls. I have a better suggestion, however: use the information that is already available to perform functional studies in order to understand the mechanism of the known associations!

Frequency of HLA-DRB1 alleles in rheumatoid arthritis patients in Zahedan, southeast Iran

BACKGROUND AND OBJECTIVES

Analysis of the role of different alleles of human leukocyte antigen (HLA) in rheumatoid arthritis (RA) patients is necessary in many populations and geographical areas. The aim of the present study was to investigate the frequency of HLA-DRB1 alleles in RA patients, comparing with that in control group in southeast Iran.

DESIGN AND SETTING

Case-control study of rheumatoid arthritis patients referred to rheumatology clinic at university hospital.

PATIENTS AND METHODS

The frequency of HLA-DRB1 alleles was determined in 79 RA patients and 93 healthy subjects in Zahedan, southeast Iran. HLA-DRB1 allele types were identified by polymerase chain reaction with sequence-specific primer (PCR-SSP).

RESULTS

The HLA-DRB1FNx0110 allele showed a significantly higher frequency in patients with RA (OR=2.698, 95% CI=1.087-6.699, P=.045), while the frequency of DRB1FNx0103 allele in these subjects was significantly lower than that in the control group (OR=0.447, 95% CI=0.2285-0.8729, P=.021). The frequencies of DRB1FNx0101, DRB1FNx0104, DRB1FNx0107, DRB1FNx0109, DRB1FNx0111, DRB1FNx0113, DRB1FNx0114, DRB1FNx0115, DRB1FNx0116 were not significantly different between RA subjects and the control group.

CONCLUSION

The data suggest that the DRB1FNx0110 allele is a risk factor and DRB1FNx0103 is protective for RA in this population.

Polymerase chain reaction (PCR) and sequence specific oligonucleotide probes (SSOP) genotyping assay for detection of genes associated with rheumatoid arthritis and multiple sclerosis

In this paper an assay for the detection of genes associated with rheumatoid arthritis (RA) and multiple sclerosis, using polymerase chain reaction (PCR) and sequence specific oligonucleotide probes (SSOP) is presented, in order to be further applied in a portable Lab-On-Chip (LOC) device. A substantial part of these reagents were based on the literature (11th International Histocompatibility Workshop, IHW), bearing the advantage of proven successful implementation in genotyping, while others were designed for this study. More precisely, our methodology discriminates HLA-DRB1 as DRB1*01, *04 and *10, which include shared epitope (SE) alleles associated with RA and additionally DRB1*15 allele, including DRB1*1501 associated with MS (broad genotyping method). To further present the basic elements of the assay for high resolution genotyping of SE DRB1 alleles, we provide as an example the case of HLA-DRB1*10 alleles (HLADRB1* 100101, *100102, *100103, *1002 and *1003). Regarding the methodology for developing a detection assay, for SNPs associated with RA or MS the basic steps are presented. DNA sequence data are obtained from IMGT/HLA and SNP database. Online software tools are used to define hybridization specificity of primers and probes towards human DNA, leading to hybridization patterns that uniquely designate a target allele and evaluate parameters influencing PCR efficiency. Respecting current technological limitations of autonomous molecular-based LOC systems the approach of broad genotyping of HLA-DRB1*01/*04/*10/*15 genes, is intended to be initially used, leaving, high resolution genotyping of SE alleles for future implementations. This method is easy to be updated and extended to detect additional associated loci with RA or MS.