Identification of the NF-κB activating protein-like locus as a risk locus for rheumatoid arthritis

MicroRNA-106b Overexpression Suppresses Synovial Inflammation and Alleviates Synovial Damage in Patients with Rheumatoid Arthritis

OBJECTIVES

To explore the effect of miR-106b on synovial inflammation and damage in rheumatoid arthritis (RA) patients, and further to investigate its possible mechanism.

METHODS

: Quantitative real-time polymerase chain reaction (qRT-PCR), immunofluorescence, in situ hybridization and immunohistochemistry assay were separately used to verify the levels of miR-106b and cytokines in the synovial tissues of patients with RA or osteoarthritis (OA). Pearson correlation analysis was conducted to examine the bivariate relationship between miR-106b and cytokines or RANKL. Following the isolation and culture of fibroblast-like synoviocytes (FLS), the cells were transfected with lentivirus-mediated miR-106b mimic, miR-106b inhibitor, and negative control miR-106b mimic, respectively. Thereafter, cell proliferation was measured by Cell Counting Kit-8 assay, and cell invasion and migration capacity was assessed by Transwell assay. Furthermore, concentration and expression of cytokines were separately detected by Enzyme linked immunosorbent assay and Western blot.

RESULTS

Compared with osteoarthritis, validation by qRT-PCR showed that RA patients had a lower level of miR-106b and higher levels of receptor activator of nuclear factor-κ B ligand (RANKL), tumor necrosis factor-a (TNF-a) and interleukin-6 (IL-6). Additionally, the scatter plot showed that the relative transcription of miR-106b level was negatively correlated to the level of TNF-a, IL-6, and RNKAL in the synovial tissues of both RA and OA patients (All P<0.05). Furthermore, miR-106b overexpression suppressed cell proliferation, migration and invasion capacity of human RA-FLS.

CONCLUSIONS

miR-106b overexpression suppresses synovial inflammation and alleviates synovial damage, thus it may be served as a potential therapeutic target for RA patients.

The ZNF76 rs10947540 polymorphism associated with systemic lupus erythematosus risk in Chinese populations

Systemic lupus erythematosus (SLE) is a typical autoimmune disease with a strong genetic disposition. Genetic studies have revealed that single-nucleotide polymorphisms (SNPs) in zinc finger protein (ZNF)-coding genes are associated with susceptibility to autoimmune diseases, including SLE. The objective of the current study was to evaluate the correlation between ZNF76 gene polymorphisms and SLE risk in Chinese populations. A total of 2801 individuals (1493 cases and 1308 controls) of Chinese Han origin were included in this two-stage genetic association study. The expression of ZNF76 was evaluated, and integrated bioinformatic analysis was also conducted. The results showed that 28 SNPs were associated with SLE susceptibility in the GWAS cohort, and the association of rs10947540 was successfully replicated in the independent replication cohort (P_replication = 1.60 × 10^-2, OR 1.19, 95% CI 1.03-1.37). After meta-analysis, the association between rs10947540 and SLE was pronounced (P_meta = 9.62 × 10^-6, OR 1.29, 95% CI 1.15-1.44). Stratified analysis suggested that ZNF76 rs10947540 C carriers were more likely to develop relatively high levels of serum creatinine (Scr) than noncarriers (CC + CT vs. TT, p = 9.94 × 10^-4). The bioinformatic analysis revealed that ZNF76 rs10947540 was annotated as an eQTL and that rs10947540 was correlated with decreased expression of ZNF76. Remarkably, significantly reduced expression of ZNF76 was confirmed by expression data from both our laboratory and an array-based expression database. Taken together, these results suggest that ZNF76 rs10947540 is a possible susceptibility factor associated with SLE susceptibility. The mechanism underlying the relationship between ZNF76 and SLE pathogenesis still requires further investigation.

Relieving Sore Throat Formula Exerts a Therapeutic Effect on Pharyngitis through Immunoregulation and NF-κB Pathway

Relieving Sore Throat Formula (RSTF) is a formula approved by the China Food and Drug Administration and has been used for the treatment of pharyngitis in clinic for many years. However, the potential pharmacological mechanism still remains unknown. We combined multiple methods including bioinformatics data digging, network pharmacology analysis, and pathway analysis to predict the potential target of RSTF. We verified our in silico prediction results with an in vivo/vitro antibacterial effect test, mouse phagocytic index test, proliferation, transformation, and migration of mouse spleen lymphocytes. Alteration of NF-κB pathway was determined by Western blotting, immunofluorescence, and PCR. The in vivo experiments demonstrated that the RSTF could significantly relieve the symptoms of pharyngitis. A rat saliva secretion test showed that RSTF can effectively relieve the xerostomia symptom. A phenol red excretion test showed that RSTF has an eliminating phlegm effect. A hot plate method and granuloma experiment proved that RSTF also have analgesic and anti-inflammatory effects. In silico prediction demonstrates that 70 active compounds of RSTF were filtered out through ADME screening and 84 putative targets correlated with different diseases. Pathway enrichment analysis showed that the candidate targets were mostly related to the response to bacteria and immunity signalling pathways, which are known contributors to pharyngitis. Experimental results confirmed that RSTF exerted therapeutic effects on pharyngitis mainly by antibacterial effect and downregulation of NF-κB activities. It is demonstrated both in silico and in vivo/vitro that RSTF exerted therapeutic effects on pharyngitis mainly through an antibiotic effect and downregulation of NF-κB signalling pathway.

Studying the effects of haplotype partitioning methods on the RA-associated genomic results from the North American Rheumatoid Arthritis Consortium (NARAC) dataset

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Haplotype blocks methods plays a complementary role to the single-SNP approaches.

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CIT, FGT, SSLD, and single-SNP methods should be applied to discover the markers.

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Selection of the method used for the association has an impact on the biomarkers.

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SSLD method detected more significant SNPs than CIT, FGT, and single-SNP methods.

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The 383 SNPs discovered by all methods are significantly associated with RA.

The human genome, which includes thousands of genes, represents a big data challenge. Rheumatoid arthritis (RA) is a complex autoimmune disease with a genetic basis. Many single-nucleotide polymorphism (SNP) association methods partition a genome into haplotype blocks. The aim of this genome wide association study (GWAS) was to select the most appropriate haplotype block partitioning method for the North American Rheumatoid Arthritis Consortium (NARAC) dataset. The methods used for the NARAC dataset were the individual SNP approach and the following haplotype block methods: the four-gamete test (FGT), confidence interval test (CIT), and solid spine of linkage disequilibrium (SSLD). The measured parameters that reflect the strength of the association between the biomarker and RA were the P-value after Bonferroni correction and other parameters used to compare the output of each haplotype block method. This work presents a comparison among the individual SNP approach and the three haplotype block methods to select the method that can detect all the significant SNPs when applied alone. The GWAS results from the NARAC dataset obtained with the different methods are presented. The individual SNP, CIT, FGT, and SSLD methods detected 541, 1516, 1551, and 1831 RA-associated SNPs respectively, and the individual SNP, FGT, CIT, and SSLD methods detected 65, 156, 159, and 450 significant SNPs respectively, that were not detected by the other methods. Three hundred eighty-three SNPs were discovered by the haplotype block methods and the individual SNP approach, while 1021 SNPs were discovered by all three haplotype block methods. The 383 SNPs detected by all the methods are promising candidates for studying RA susceptibility. A hybrid technique involving all four methods should be applied to detect the significant SNPs associated with RA in the NARAC dataset, but the SSLD method may be preferred because of its advantages when only one method was used.

Comparative study for haplotype block partitioning methods - Evidence from chromosome 6 of the North American Rheumatoid Arthritis Consortium (NARAC) dataset

Haplotype-based methods compete with “one-SNP-at-a-time” approaches on being preferred for association studies. Chromosome 6 contains most of the known genetic biomarkers for rheumatoid arthritis (RA) disease. Therefore, chromosome 6 serves as a benchmark for the haplotype methods testing. The aim of this study is to test the North American Rheumatoid Arthritis Consortium (NARAC) dataset to find out if haplotype block methods or single-locus approaches alone can sufficiently provide the significant single nucleotide polymorphisms (SNPs) associated with RA. In addition, could we be satisfied with only one method of the haplotype block methods for partitioning chromosome 6 of the NARAC dataset? In the NARAC dataset, chromosome 6 comprises 35,574 SNPs for 2,062 individuals (868 cases, 1,194 controls). Individual SNP approach and three haplotype block methods were applied to the NARAC dataset to identify the RA biomarkers. We employed three haplotype partitioning methods which are confidence interval test (CIT), four gamete test (FGT), and solid spine of linkage disequilibrium (SSLD). P-values after stringent Bonferroni correction for multiple testing were measured to assess the strength of association between the genetic variants and RA susceptibility. Moreover, the block size (in base pairs (bp) and number of SNPs included), number of blocks, percentage of uncovered SNPs by the block method, percentage of significant blocks from the total number of blocks, number of significant haplotypes and SNPs were used to compare among the three haplotype block methods. Individual SNP, CIT, FGT, and SSLD methods detected 432, 1,086, 1,099, and 1,322 associated SNPs, respectively. Each method identified significant SNPs that were not detected by any other method (Individual SNP: 12, FGT: 37, CIT: 55, and SSLD: 189 SNPs). 916 SNPs were discovered by all the three haplotype block methods. 367 SNPs were discovered by the haplotype block methods and the individual SNP approach. The P-values of these 367 SNPs were lower than those of the SNPs uniquely detected by only one method. The 367 SNPs detected by all the methods represent promising candidates for RA susceptibility. They should be further investigated for the European population. A hybrid technique including the four methods should be applied to detect the significant SNPs associated with RA for chromosome 6 of the NARAC dataset. Moreover, SSLD method may be preferred for its favored benefits in case of selecting only one method.

Identification of rheumatoid arthritis biomarkers based on single nucleotide polymorphisms and haplotype blocks: A systematic review and meta-analysis

Genetics of autoimmune diseases represent a growing domain with surpassing biomarker results with rapid progress. The exact cause of Rheumatoid Arthritis (RA) is unknown, but it is thought to have both a genetic and an environmental bases. Genetic biomarkers are capable of changing the supervision of RA by allowing not only the detection of susceptible individuals, but also early diagnosis, evaluation of disease severity, selection of therapy, and monitoring of response to therapy. This review is concerned with not only the genetic biomarkers of RA but also the methods of identifying them. Many of the identified genetic biomarkers of RA were identified in populations of European and Asian ancestries. The study of additional human populations may yield novel results. Most of the researchers in the field of identifying RA biomarkers use single nucleotide polymorphism (SNP) approaches to express the significance of their results. Although, haplotype block methods are expected to play a complementary role in the future of that field.