Effect of MTHFR, TGFβ1, and TNFB polymorphisms on osteoporosis in rheumatoid arthritis patients

Cytokine patterns in the blister fluid and plasma of patients with fracture blisters

BACKGROUND

Fracture blister (FB) is a complication of fracture, which damages to the skin integrity and increases the risk of infection. Inflammation plays an important role in the formation and development of FBs, but its specific mechanism is still unclear. The aim of this study was to investigate the patterns and dynamic changes of inflammatory cytokines in fracture blister fluid (FBF) and plasma.

MATERIALS AND METHODS

FBF and plasma were collected simultaneously from patients with lower extremity fractures with FBs on the first and fifth day after blisters formation. 92 inflammation-related protein biomarkers were measured in plasma and FBF using Proximity Extension Assay (PEA). We analyzed the cytokine patterns and their dynamic changes in FBF and plasma. Cytokine patterns in plasma from FB patients, fracture without blister patients, and healthy subjects were also analyzed.

RESULT

The cytokine pattern in FBF and plasma of patients with FBs was different but 11 cytokines were significantly correlated in the two sample types. 23 cytokines were different in plasma across FB patients, fracture without blister patients and healthy subjects. In the analysis of plasma from FB patients and fracture without blister patients, 15 cytokines were significantly different and they may be potential risk factors for the occurrence of FBs. The FBF and plasma showed different cytokine patterns in the early and late stages, with 50 cytokines significantly changed in FBF and 20 cytokines in plasma.

CONCLUSION

The different cytokine patterns in plasma between FB patients and fracture without blisters patients may be the potential factors for the occurrence of blisters. The cytokine patterns in FBF and plasma showed a dynamic change from the inflammatory stage to the proliferative and repair stage, which indicates that FBs may have new clinical importance in addition to being a soft tissue injury.

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

•

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

•

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

•

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

•

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

•

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.

MicroRNA-214-5p/TGF-β/Smad2 signaling alters adipogenic differentiation of bone marrow stem cells in postmenopausal osteoporosis

Postmenopausal osteoporosis (OPM) is a common type of osteoporosis in females. It is a systemic, chronic bone disease that presents as microstructure degradation of osseous tissue, decreased bone mineral density and increased osteopsathyrosis caused by hypoovarianism and reduced estrogen levels in the body following menopause. In the present study, the role of microRNA (miR)-214-5p in the regulation of the expression of bone marrow stem cells (BMSCs) was investigated, and its molecular mechanism of osteogenic induction in vitro was assessed. When dexamethasone-induced adipogenic differentiation was performed, miR-214-5p expression was increased compared with the control group, as determined by RT-qPCR. Furthermore, oil red O staining, RT-qPCR and western blot analysis demonstrated that overexpression of miR-214-5p promoted adipogenic differentiation, inhibited alkaline phosphatase (ALP), runt-related transcription factor 2 (Runx2), osteocalcin (OC) and collagen α-1 (I) chain (COL1A1) mRNA expression, and suppressed transforming growth factor (TGF)-β, phosphorylated (p)-Smad2 and collagen type IV α1 chain (COL4A1) protein expression in BMSCs. Additionally, downregulation of miR-214-5p increased the ALP, Runx2, OC and COL1 mRNA expression and increased TGF-β, Smad2 and COL4A1 protein expression in BMSCs. Furthermore, a TGF-β inhibitor was employed to inhibit TGF-β expression in BMSCs following miR-214-5p downregulation, which led to reduced Smad2, TGF-β and COL4A1 protein expression, and ALP, Runx2, OC and COL1 mRNA expression was also reduced, compared with the miR-214-5p downregulation only group. It was demonstrated that miR-214-5p may weaken osteogenic differentiation of BMSCs through regulating COL4A1. In conclusion, the results of the present study indicated that miR-214-5p may promote the adipogenic differentiation of BMSCs through regulation of the TGF-β/Smad2/COL4A1 signaling pathway, and potentially may be used to develop a novel drug for postmenopausal osteoporosis.

MTRR A66G, RFC1 G80A, and MTHFR C677T and A1298C Polymorphisms and Disease Activity in Mexicans with Rheumatoid Arthritis Treated with Methotrexate

Aim: To investigate the relationships of polymorphisms in genes whose protein products are related in the metabolic pathway of folic acid, particularly MTRR A66G, RFC1 G80A, and MTHFR C677T and A1298C, and disease activity in Mexican patients with rheumatoid arthritis (RA) treated with methotrexate (MTX).

Materials and Methods: Sixty-eight patients with RA were included in the study who were being treated with MTX, either with or without other drugs. In addition to general data, disease activity was measured by the disease activity score 28 (DAS28). Single nucleotide polymorphisms (SNPs) genotyping was performed by allelic discrimination using real-time polymerase chain reaction.

Results: Differences in genotype (homozygotic or heterozygotic for each allele), allele distributions, and phenotype were not statistically different between the RA group and control populations. We did not find any association between the studied polymorphisms and disease activity nor with the intragroup variables (e.g., clinical activity, body mass index, and single- or combined-drug treatment) or between genetic markers; we also did not find any association within the RA group or between the RA group and control populations.

Conclusion: Additional studies of more polymorphisms related to this or other metabolic pathways are required to determine the influence of genetics on disease activity in RA.

Polymorphisms of -800G/A and +915G/C in TGF-β1 gene and lung cancer susceptibility

We studied the relationship between the polymorphisms of −800G/A and +915G/C in transforming growth factor-β1 (TGF-β1) gene and lung cancer susceptibility. The sequence-specific primer polymerase chain reaction (PCR-SSP) technique was used to test 156 non-small cell lung cancer (NSCLC) patients that were selected as the observation group and 156 patients with pneumonia and tuberculosis that were selected as the control group (age and gender 1:1 proximal matching principle) and the polymorphisms of the first exon −800G/A and +915G/C TGF-β1 genes. The expression of TGF-β1 levels in peripheral blood was detected using ELISA. The proportion of −800G/A gene AA subtype and A allelic gene in the observation group was significantly higher than that in the control group, while the proportion of +915G/C gene CC subtype and C allelic gene was also significantly higher than that in the control group (P<0.05). The cancer risk [odds ratio (OR)] of patients with A allelic gene in −800G/A gene was 4.8 (95% CI=2.563–6.537, P<0.05), while the cancer risk (OR) of patients with C allelic gene in +915G/C gene was 4.7 (95% CI=2.317–5.864, P<0.05). The serum TGF-β1 expression levels of −800G/A gene AA subtype in the observation group was significantly higher than the GG type, GA type and the control group, while the TGF-β1 level of +915G/C gene CC subtype was significantly higher than the GG type, GC type and the control group (P<0.05). Therefore, the polymorphisms of −800G/A and +915G/C in TGF-β1 gene are closely related to the lung cancer susceptibility.

Genetic Case-Control Study for Eight Polymorphisms Associated with Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an autoimmune disease which has a significant socio-economic impact. The aim of the current study was to investigate eight candidate RA susceptibility loci to identify the associated variants in Egyptian population. Eight single nucleotide polymorphisms (SNPs) (MTHFR—C677T and A1298C, TGFβ1 T869C, TNFB A252G, and VDR—ApaI, BsmI, FokI, and TaqI) were tested by genotyping patients with RA (n = 105) and unrelated controls (n = 80). Associations were tested using multiplicative, dominant, recessive, and co-dominant models. Also, the linkage disequilibrium (LD) between the VDR SNPs was measured to detect any indirect association. By comparing RA patients with controls (TNFB, BsmI, and TaqI), SNPs were associated with RA using all models. MTHFR C677T was associated with RA using all models except the recessive model. TGFβ1 and MTHFR A1298C were associated with RA using the dominant and the co-dominant models. The recessive model represented the association for ApaI variant. There were no significant differences for FokI and the presence of RA disease by the used models examination. For LD results, There was a high D′ value between BsmI and FokI (D′ = 0.91), but the r² value between them was poor. All the studied SNPs may contribute to the susceptibility of RA disease in Egyptian population except for FokI SNP.