Genetic associations with radiological damage in rheumatoid arthritis: Meta-analysis of seven genome-wide association studies of 2,775 cases

Gene selection by incorporating genetic networks into case-control association studies

Large-scale genome-wide association studies (GWAS) have been successfully applied to a wide range of genetic variants underlying complex diseases. The network-based regression approach has been developed to incorporate a biological genetic network and to overcome the challenges caused by the computational efficiency for analyzing high-dimensional genomic data. In this paper, we propose a gene selection approach by incorporating genetic networks into case-control association studies for DNA sequence data or DNA methylation data. Instead of using traditional dimension reduction techniques such as principal component analyses and supervised principal component analyses, we use a linear combination of genotypes at SNPs or methylation values at CpG sites in a gene to capture gene-level signals. We employ three linear combination approaches: optimally weighted sum (OWS), beta-based weighted sum (BWS), and LD-adjusted polygenic risk score (LD-PRS). OWS and LD-PRS are supervised approaches that depend on the effect of each SNP or CpG site on the case-control status, while BWS can be extracted without using the case-control status. After using one of the linear combinations of genotypes or methylation values in each gene to capture gene-level signals, we regularize them to perform gene selection based on the biological network. Simulation studies show that the proposed approaches have higher true positive rates than using traditional dimension reduction techniques. We also apply our approaches to DNA methylation data and UK Biobank DNA sequence data for analyzing rheumatoid arthritis. The results show that the proposed methods can select potentially rheumatoid arthritis related genes that are missed by existing methods.

Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis

Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10-8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.

Polygenic risk scores are associated with radiographic progression in patients with rheumatoid arthritis

OBJECTIVE

To investigate whether polygenic risk score (PRS) using data from a genome-wide association study (GWAS) for rheumatoid arthritis (RA) susceptibility can be a predictor for radiographic progression.

METHODS

We constructed the PRS using GWAS summary data for disease susceptibility to predict Sharp/van der Heijde score (SHS) changes in first five years from the onset (the top quartile of SHS changes was defined as severe progression and the remaining as non-severe progression). We selected the best model in a training set (n = 500) and validated it in a testing set (n = 740). We evaluated the performance of PRS in univariable and multivariable analyses with other factors to predict severe progression.

RESULTS

PRS constructed of 43,784 SNPs significantly differed between severe and non-severe progression in both training (P = 0.0064) and testing sets (P = 0.017). The patients with the top quintile PRS had a higher risk for severe progression compared to those with the bottom quintile (odds ratio (OR) 1.90, P = 0.0022), which was higher when restricted to younger-onset patients (OR 5.06, P = 0.00038). The top quintile PRS and ACPAs positive groups had significantly higher proportion of patients with severe progression compared to the remaining groups (P = 0.00052, and 0.0022, respectively). Multivariable analysis showed that PRS (P = 0.00019) as well as sex (female) (P = 0.0033), ACPAs (P = 0.0023), and BMI (P = 0.031) were independent risk factors.

CONCLUSION

PRS using GWAS data for RA susceptibility is associated with radiographic progression.

The Clinical Course of Rheumatoid Arthritis in Kazakhstani Patients

BACKGROUND: Rheumatoid arthritis (RA) prevalence according to the worldwide epidemiological data varies from 0.4% to 1.3%. The disability and mortality rate in RA is high. RA clinic is various, and compiles from articular and systemic manifestations. AIM: The aim of our study was to investigate the clinical course of RA in Kazakhstani patients living in North region of our country. METHODS: The 81 women at the age of 30–55 years with a verified diagnosis of RA who have lived in Kazakhstan for at least 10 years were recruited to the study. All participants were examined by the rheumatologist and a standard laboratory examination was carried out. Statistical analysis was conducted in IBM SPSS Statistics 26 software (IBM.USA;1). RESULTS: The statistically significant higher frequency of erosive radiological stages, bone ankylosis (χ2 = 18.070 df = 6 p = 0.005) was found in seropositive (rheumatoid factor [RF]+) anti-citrullinated protein/peptide antibody positive (ACPA+) subgroup. The correlation analysis showed strong association between certain RA form activity and inflammatory markers, as well as disease triggers. The discriminant model which predicts the stage of radiological damage was obtained. The sensitivity of model in predicting X-ray Stage I-71.6%, Stage II-29.4%, Stage III-37.5%, and Stage IV-63.6%. CONCLUSION: The debut of the RA on average occurred in the third decade of the patients’ life. The joint syndrome had a more unfavorable character RF+ACPA+ patients’ subgroup; however, RF+ACPA-negative (ACPA-) subgroup also showed a predisposition to poorer prognosis. The obtained discriminant model may be useful for RA patients’ management.

Association of AFF3 Gene Polymorphism rs10865035 with Rheumatoid Arthritis: A Population-Based Case-Control Study on a Pakistani Cohort

Rheumatoid arthritis (RA) is one of the complex diseases with the involvement of the genetic as well as environmental factors in its onset and severity. Different genome-wide association and candidate gene studies have shown the role of several genetic variants in multiple loci/genes with ethnical and geographical variations. This study was designed to detect the association of a single-nucleotide polymorphism (SNP) rs10865035 in the AFF3 gene with the genetic background of rheumatoid arthritis (RA) in the Pakistani cohort. A total of 703 individuals, including 409 RA patients and 294 healthy controls, were genotyped using TaqMan assay and Tri primer ARMS-PCR (amplification-refractory mutation system-polymerase chain reaction) methods. The association of rs10865035 with the RA was statistically determined using different models. Interestingly, besides the homozygous recessive model (G/G vs. A/G + A/A) (OR = 1.693(1.06-2.648); P = 0.025), all other models, which included the codominant (χ 2 = 5.169; P = 0.075), homozygous dominant (A/A vs. G/G + A/G) (OR = 0.867 (0.636-1.187); P = 0.41), heterozygous (A/G vs. A/A + GG) (OR = 0.491 (0.667-1.215); P = 0.49), and additive model (OR = 0.826 (0.665-1.027); P = 0.08) showed insignificant distribution of the genotypes among the cases and controls. These findings suggest that the AFF3 gene (rs10865035) has no significant role in the onset of RA in the Pakistani population.

Biologic Drugs for Rheumatoid Arthritis in the Context of Biosimilars, Genetics, Epigenetics and COVID-19 Treatment

Rheumatoid arthritis (RA) affects around 1.2% of the adult population. RA is one of the main reasons for work disability and premature retirement, thus substantially increasing social and economic burden. Biological disease-modifying antirheumatic drugs (bDMARDs) were shown to be an effective therapy especially in those rheumatoid arthritis (RA) patients, who did not adequately respond to conventional synthetic DMARD therapy. However, despite the proven efficacy, the high cost of the therapy resulted in limitation of the widespread use and unequal access to the care. The introduction of biosimilars, which are much cheaper relative to original drugs, may facilitate the achievement of the therapy by a much broader spectrum of patients. In this review we present the properties of original biologic agents based on cytokine-targeted (blockers of TNF, IL-6, IL-1, GM-CSF) and cell-targeted therapies (aimed to inhibit T cells and B cells properties) as well as biosimilars used in rheumatology. We also analyze the latest update of bDMARDs' possible influence on DNA methylation, miRNA expression and histone modification in RA patients, what might be the important factors toward precise and personalized RA treatment. In addition, during the COVID-19 outbreak, we discuss the usage of biologicals in context of effective and safe COVID-19 treatment. Therefore, early diagnosing along with therapeutic intervention based on personalized drugs targeting disease-specific genes is still needed to relieve symptoms and to improve the quality of life of RA patients.

A genome-wide association study identifying the SNPs predictive of rapid joint destruction in patients with rheumatoid arthritis

Rheumatoid arthritis (RA) is a common chronic autoimmune disease leading to joint destruction. The aim of the present study was to identify the genomic factors predictive of susceptibility to joint destruction in patients with RA by performing a genome-wide association study of genetic variants, including single nucleotide polymorphisms (SNPs). The study sample included 228 patients with a diagnosis of RA in the past 5 years. Patients were classified into rapid (total Sharp score/years of RA, ≥50) and slow (total Sharp score/years of RA, <50) joint destruction groups for analysis. The association between the genome-wide SNP analysis and joint destruction was evaluated. The following SNPs were strongly associated with rapid radiographic joint destruction: rs2295926 (P<1x10^-7), belonging to the N-acetylgalactosaminyltransferase 12 (GALNT12) gene and rs11958855 (P<1x10^-6), belonging to the KCNN2 gene (associated with the potassium calcium-activated channel subfamily). The identification of genetic predictors of rapid joint destruction in RA (GALNT12 and KCNN2) may provide information regarding potential therapeutic targets, and this information may be used to assist in the management RA disease progression, thereby improving the functional outcomes for patients.

Genetic Polymorphisms Associated with Rheumatoid Arthritis Development and Antirheumatic Therapy Response

Rheumatoid arthritis (RA) is the most common inflammatory arthropathy worldwide. Possible manifestations of RA can be represented by a wide variability of symptoms, clinical forms, and course options. This multifactorial disease is triggered by a genetic predisposition and environmental factors. Both clinical and genealogical studies have demonstrated disease case accumulation in families. Revealing the impact of candidate gene missense variants on the disease course elucidates understanding of RA molecular pathogenesis. A multivariate genomewide association study (GWAS) based analysis identified the genes and signalling pathways involved in the pathogenesis of the disease. However, these identified RA candidate gene variants only explain 30% of familial disease cases. The genetic causes for a significant proportion of familial RA have not been determined until now. Therefore, it is important to identify RA risk groups in different populations, as well as the possible prognostic value of some genetic variants for disease development, progression, and treatment. Our review has two purposes. First, to summarise the data on RA candidate genes and the increased disease risk associated with these alleles in various populations. Second, to describe how the genetic variants can be used in the selection of drugs for the treatment of RA.

Current Understanding of an Emerging Role of HLA-DRB1 Gene in Rheumatoid Arthritis-From Research to Clinical Practice

Rheumatoid arthritis (RA) is an autoimmune disease with an unclear pathogenic mechanism. However, it has been proven that the key underlying risk factor is a genetic predisposition. Association studies of the HLA-DRB1 gene clearly indicate its importance in RA morbidity. This review presents the current state of knowledge on the impact of HLA-DRB1 gene, functioning both as a component of the patient’s genome and as an environmental risk factor. The impact of known HLA-DRB1 risk variants on the specific structure of the polymorphic HLA-DR molecule, and epitope binding affinity, is presented. The issues of the potential influence of HLA-DRB1 on the occurrence of non-articular disease manifestations and response to treatment are also discussed. A deeper understanding of the role of the HLA-DRB1 gene is essential to explore the complex nature of RA, which is a result of multiple contributing factors, including genetic, epigenetic and environmental factors. It also creates new opportunities to develop modern and personalized forms of therapy.