Rheumatoid arthritis-associated gene-gene interaction network for rheumatoid arthritis candidate genes

Association analysis of miRNA-146a and miRNA-499 polymorphisms with rheumatoid arthritis: a case-control and trio-family study

Single nucleotide polymorphism is known to alter the expression and processing of miRNAs leading to a variety of diseases including rheumatoid arthritis (RA). However, disagreement is present up to date regarding the association of miRNA-146a and miRNA-499 polymorphisms with RA. The goal of this study was to assess the association of polymorphisms at miRNA-146a and miRNA-499 with the pathogenesis of RA in patients originating from Pakistan. Initially, eleven hundred subjects (1100) comprises of 550 RA patients and 550 healthy controls were investigated in the case-control analysis. Spectrophotometric measurement of lipids and C-reactive protein was used, whereas interleukin-1 receptor associated kinase-1 and TNF-receptor associated factor-6 values were quantified by an enzyme-linked immunosorbent assay. Secondly, heritability of susceptible alleles was tested from 70 trio-families. The miRNA-146a rs2910164 and miRNA-499 rs3746444 polymorphisms were genotyped using the polymerase chain reaction followed by restriction digestion. A Significant association of miRNA-146a and miRNA-499 genotypes was observed with RA patients (P < 0.05, respectively). The miRNA-146a rs2910164 G (OR = 1.4, P < 0.05) and miRNA-499 rs3746444 C (OR = 1.6, P < 0.0001) allele was significantly associated with RA in comparison with controls, respectively. Besides, the transmission analysis revealed a significant (P < 0.05) inheritance of rs2910164 G and rs3746444 C allele from parents to affected offspring. The current research concludes that miRNA-146a (rs2910164; C > G) and miRNA-499 (rs3746444; T > C) polymorphisms are linked to RA in the population studied. Furthermore, it was demonstrated for the first time in our high-risk cohort that the rs2910164 G and rs3746444 C allele was strongly related to familial RA.

Association between miRNA-499 gene polymorphism and autoimmune diseases: A meta-analysis

Introduction

The association between miRNA-499 rs3746444 and a variety of autoimmune diseases has been reported. However, these results were contradictory and just focused on one or two autoimmune diseases. The present study aims to examine the possible association between rs3746444 polymorphism and the risk of autoimmune diseases.

Methods

The studies that evaluated the association between miRNA-499 gene polymorphism and autoimmune diseases were retrieved. Five different genetic models were used to evaluate the association. The random-effects model was used to pool the effect sizes. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the associations. Stratification analyses were performed by ethnicity and type of autoimmune diseases. False-positive report probability (FPRP) was performed for determining noteworthy associations.

Results

Seventeen articles (twenty studies) involving 4,376 cases and 4,991 controls were identified and included in our meta-analysis. The pooled ORs of all eligible case-control studies indicated a significant association between miRNA-499 gene polymorphism and autoimmune diseases: (T vs. C: OR = 0.877; 95% CI: 0.774, 0.993; P = 0.039). Stratified analysis indicated a significant association across both Caucasian (TT vs. TC+CC: OR = 0.779; 95% CI: 0.622, 0.976; P = 0.030) and Asian (T vs. C: OR = 0.895; 95% CI: 0.808, 0.992; P = 0.035) populations. There was also a significant association in Behcet’s disease, rheumatoid arthritis, systemic lupus erythematosus, and ulcerative colitis populations.

Conclusions

Our meta-analysis suggested that the miRNA-499 rs3746444 polymorphism was associated with an elevated risk of autoimmune diseases in the overall analysis as well as Caucasian and Asian populations.

Modified entropy-based procedure detects gene-gene-interactions in unconventional genetic models

BACKGROUND

Since it is assumed that genetic interactions play an important role in understanding the mechanisms of complex diseases, different statistical approaches have been suggested in recent years for this task. One interesting approach is the entropy-based IGENT method by Kwon et al. that promises an efficient detection of main effects and interaction effects simultaneously. However, a modification is required if the aim is to only detect interaction effects.

METHODS

Based on the IGENT method, we present a modification that leads to a conditional mutual information based approach under the condition of linkage equilibrium. The modified estimator is investigated in a comprehensive simulation based on five genetic interaction models and applied to real data from the genome-wide association study by the North American Rheumatoid Arthritis Consortium (NARAC).

RESULTS

The presented modification of IGENT controls the type I error in all simulated constellations. Furthermore, it provides high power for detecting pure interactions specifically on unconventional genetic models both in simulation and real data.

CONCLUSIONS

The proposed method uses the IGENT software, which is free available, simple and fast, and detects pure interactions on unconventional genetic models. Our results demonstrate that this modification is an attractive complement to established analysis methods.

HLA-C: An Accomplice in Rheumatic Diseases

Human leukocyte antigen c (HLA-C) is a polymorphic membrane protein encoded by the HLA-C gene in the class I major histocompatibility complex. HLA-C plays an essential role in protection against cancer and viruses but has also been implicated in allograft rejection, preeclampsia, and autoimmune disease. This review summarizes reports and proposed mechanisms for the accessory role of HLA-C in rheumatic diseases. Historically, contributions of HLA-C to rheumatic diseases were eclipsed by the stronger association with HLA-DRB1 alleles containing the "shared epitope" with rheumatoid arthritis. Larger genetic association studies and more powerful analytical approaches have revealed independent associations of HLA-C with rheumatic disease-associated phenotypes, including development of anticitrullinated peptide antibodies. HLA-C functions by presenting antigens to T cells and by binding activatory and inhibitory receptors on natural killer (NK) cells, but the exact mechanisms by which the HLA-C locus contributes to autoimmunity are largely undefined. Studies have suggested that HLA-C and NK cell receptor polymorphisms may predict responsiveness to pharmacotherapy. Understanding the mechanisms of the role of HLA-C in rheumatic disease could uncover therapeutic targets or guide precision pharmacologic treatments.

Genomic locus on chromosome 1 regulates susceptibility to spontaneous arthritis in mice deficiency of IL-1RA

BACKGROUND

To understand the role of genetic factors on chromosome 1 in the regulation of spontaneous arthritis in mice deficient in IL-1 receptor antagonist protein (IL_1RA), we previously used speed congenic breeding to transfer the QTL region from DBA/1(-/-) mice that are resistant to spontaneous arthritis into BALB/c(-/-) mice which are susceptible. We were able to establish two congenic strains which exhibited a delayed onset and reduced severity of disease. In this study, we asked a different set of questions. How will the QTL region from BALB/c(-/-) interact with the rest of the genome in the DBA/1(-/-) background? Will the DBA/1(-/-) mice become susceptible to spontaneous arthritis if the QTL genomic region on chromosome 1 was replaced with the genomic fragment of the same region from BALB/c(-/-)? We conducted the congenic breeding with the similar procedure as that of congenic strains with BALB/c(-/-) background.

RESULT

Instead of BALB/c(-/-), DBA/1(-/-) was used as the recurrent parent while BALB/c(-/-) was used as the donor parent. By the 6(th) generation we determined that all of the chromosomes in the progeny were of DBA/1(-/-) origin with the exception of the QTL portion of chromosome 1 which is heterozygous of BALB/c(-/-) and DBA/1(-/-) origin. We then intercrossed selected mice to produce homozygous strains containing the homozygous genomic region of BALB/c(-/-) on chromosome 1, while the rest of genome are homozygous DBA/1(-/-). This strain was observed for the development of spontaneous arthritis. Up to 9 weeks of age, both congenic strain and DBA/1(-/-) did not develop arthritis. However, after 9 weeks, the congenic strain started to exhibit signs of arthritis, while the DBA/1(-/-) remained free from disease.

CONCLUSION

The result indicates a strong influence of genetic factor(s) on the QTL of chromosome 1 on the susceptibility to spontaneous arthritis. Identification of genetic factors within this QTL region in the future will significantly enhance our understanding of molecular mechanism of spontaneous arthritis.

A partition-based approach to identify gene-environment interactions in genome wide association studies

It is believed that almost all common diseases are the consequence of complex interactions between genetic markers and environmental factors. However, few such interactions have been documented to date. Conventional statistical methods for detecting gene and environmental interactions are often based on the linear regression model, which assumes a linear interaction effect. In this study, we propose a nonparametric partition-based approach that is able to capture complex interaction patterns. We apply this method to the real data set of hypertension provided by Genetic Analysis Workshop 18. Compared with the linear regression model, the proposed approach is able to identify many additional variants with significant gene-environmental interaction effects. We further investigate one single-nucleotide polymorphism identified by our method and show that its gene-environmental interaction effect is, indeed, nonlinear. To adjust for the family dependence of phenotypes, we apply different permutation strategies and investigate their effects on the outcomes.

A robust model-free approach for rare variants association studies incorporating gene-gene and gene-environmental interactions

Recently more and more evidence suggest that rare variants with much lower minor allele frequencies play significant roles in disease etiology. Advances in next-generation sequencing technologies will lead to many more rare variants association studies. Several statistical methods have been proposed to assess the effect of rare variants by aggregating information from multiple loci across a genetic region and testing the association between the phenotype and aggregated genotype. One limitation of existing methods is that they only look into the marginal effects of rare variants but do not systematically take into account effects due to interactions among rare variants and between rare variants and environmental factors. In this article, we propose the summation of partition approach (SPA), a robust model-free method that is designed specifically for detecting both marginal effects and effects due to gene-gene (G×G) and gene-environmental (G×E) interactions for rare variants association studies. SPA has three advantages. First, it accounts for the interaction information and gains considerable power in the presence of unknown and complicated G×G or G×E interactions. Secondly, it does not sacrifice the marginal detection power; in the situation when rare variants only have marginal effects it is comparable with the most competitive method in current literature. Thirdly, it is easy to extend and can incorporate more complex interactions; other practitioners and scientists can tailor the procedure to fit their own study friendly. Our simulation studies show that SPA is considerably more powerful than many existing methods in the presence of G×G and G×E interactions.

New insights into the genetics of immune responses in rheumatoid arthritis

Rheumatoid arthritis (RA) is a common autoimmune disease with a strong genetic component. Numerous aberrant immune responses have been described during the evolution of the disease. In later years, the appearance of anti-citrullinated protein antibodies (ACPAs) has become a hallmark for the diagnosis and prognosis of RA. The post-translational transformation of arginine residues of proteins and peptides into citrulline (citrullination) is a natural process in the body, but for unknown reasons autoreactivity towards citrullinated residues may develop in disposed individuals. ACPAs are often found years before clinical manifestations. ACPAs are present in about 70% of RA patients and constitute an important disease marker, distinguishing patient groups with different prognoses and different responses to various treatments. Inside the human leukocyte antigen (HLA) region, some HLA-DRB1 alleles are strongly associated with their production. Genome-wide association studies in large patient cohorts have defined a great number of single nucleotide polymorphisms (SNPs) outside of the HLA region that are associated with ACPA positive (ACPA+) RA. The SNPs are generally located close to or within genes involved in the immune response or signal transduction in immune cells. Some environmental factors such as tobacco smoking are also positively correlated with ACPA production. In this review, we will describe the genes and loci associated with ACPA+ RA or ACPA- RA and attempt to clarify their potential role in the development of the disease.

Traditional chinese medicine-based network pharmacology could lead to new multicompound drug discovery

Current strategies for drug discovery have reached a bottleneck where the paradigm is generally “one gene, one drug, one disease.” However, using holistic and systemic views, network pharmacology may be the next paradigm in drug discovery. Based on network pharmacology, a combinational drug with two or more compounds could offer beneficial synergistic effects for complex diseases. Interestingly, traditional chinese medicine (TCM) has been practicing holistic views for over 3,000 years, and its distinguished feature is using herbal formulas to treat diseases based on the unique pattern classification. Though TCM herbal formulas are acknowledged as a great source for drug discovery, no drug discovery strategies compatible with the multidimensional complexities of TCM herbal formulas have been developed. In this paper, we highlighted some novel paradigms in TCM-based network pharmacology and new drug discovery. A multiple compound drug can be discovered by merging herbal formula-based pharmacological networks with TCM pattern-based disease molecular networks. Herbal formulas would be a source for multiple compound drug candidates, and the TCM pattern in the disease would be an indication for a new drug.

Detection for gene-gene co-association via kernel canonical correlation analysis

Background

Currently, most methods for detecting gene-gene interaction (GGI) in genomewide association studies (GWASs) are limited in their use of single nucleotide polymorphism (SNP) as the unit of association. One way to address this drawback is to consider higher level units such as genes or regions in the analysis. Earlier we proposed a statistic based on canonical correlations (CCU) as a gene-based method for detecting gene-gene co-association. However, it can only capture linear relationship and not nonlinear correlation between genes. We therefore proposed a counterpart (KCCU) based on kernel canonical correlation analysis (KCCA).

Results

Through simulation the KCCU statistic was shown to be a valid test and more powerful than CCU statistic with respect to sample size and interaction odds ratio. Analysis of data from regions involving three genes on rheumatoid arthritis (RA) from Genetic Analysis Workshop 16 (GAW16) indicated that only KCCU statistic was able to identify interactions reported earlier.

Conclusions

KCCU statistic is a valid and powerful gene-based method for detecting gene-gene co-association.

Association of polymorphisms in pre-miRNA with inflammatory biomarkers in rheumatoid arthritis in the Chinese Han population

The aim of this study was to detect the association between 2 single nucleotide polymorphisms (SNPs), rs2910164 G>C and rs3746444 T>C, in pre-miRNA (hsa-mir-146a and hsa-mir-499) and the chronic inflammation in the Chinese Han population with rheumatoid arthritis (RA). Two hundred sixty-two Han Chinese patients with RA were recruited in this study. The SNPs were genotyped by polymerase chain reaction restriction fragment length polymorphism. C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and the plasma concentrations of interleukin (IL)-6, tumor necrosis factor α (TNF-α), and transforming growth factor β1 (TGF-β1) were measured. There was a significant difference in the levels of CRP and ESR among different genotypes in rs3746444 (p = 0.031 and p = 0.047, respectively). The heterozygote CT had significantly higher levels of CRP and ESR compared with homozygotes CC and TT. No significant association was observed between the SNP rs2910164 and the levels of CRP, ESR, IL-6, TNF-α, and TGF-β1 (all p > 0.05). The results of this study provided the first evidence that the SNP rs3746444 in pre-miR-499 could affect the inflammatory reaction in patients with RA. The findings were significant and might contribute to the clinical assessment of inflammatory activity, which in turn may influence therapeutic decision making.

Association study of single nucleotide polymorphisms in pre-miRNA and rheumatoid arthritis in a Han Chinese population

The aim of this study was to perform an association study between two single nucleotide polymorphisms (SNPs) rs2910164 G>C and rs3746444 T>C in pre-miRNA (hsa-mir-146a and hsa-mir-499) and rheumatoid arthritis (RA) in the Han Chinese population. 208 Han Chinese patients with RA and 240 healthy controls were recruited in this study. The SNPs was genotyped by polymerase chain reaction-restriction fragment length polymorphism. Anti-cyclic citrullinated peptide (anti-CCP) antibody was measured by enzyme linked immunosorbent assay and rheumatoid factor (RF) was measured by rate nephelometry. The genotype frequencies between cases and controls were compared by χ(2) analysis. No significant association between the SNPs (rs2910164 and rs3746444) and RA was observed (P = 0.631 and 0.775, respectively), and the SNPs did not show any association with the RF-positive (P = 0.631 and 0.775, respectively). However, there was a significant difference on the level of anti-CCP antibody between different genotypes in rs3746444 (P = 0.007). The heterozygote CT had significantly higher level of anti-CCP antibody compared with homozygote CC and TT (P = 0.054 and 0.003, respectively). We first investigated the association between the SNPs (rs2910164 G>C and rs3746444 T>C) in the pre-miRNA (hsa-mir-146a and hsa-mir-499) and RA in a Han Chinese population. We did not find a significant association between the SNPs and the susceptibility to RA, while the SNP rs3746444 may affect anti-CCP antibody production.

The challenge of detecting epistasis (G x G interactions): Genetic Analysis Workshop 16

Interest is increasing in epistasis as a possible source of the unexplained variance missed by genome-wide association studies. The Genetic Analysis Workshop 16 Group 9 participants evaluated a wide variety of classical and novel analytical methods for detecting epistasis, in both the statistical and machine learning paradigms, applied to both real and simulated data. Because the magnitude of epistasis is clearly relative to scale of penetrance, and therefore to some extent, to the choice of model framework, it is not surprising that strong interactions under one model might be minimized or even disappear entirely under a different modeling framework.