Lack of Association Between TNF-α, IFN-γ, IL-10 Gene Polymorphisms and Rheumatic Heart Disease in South Indian Population

The microbiome and rheumatic heart disease: current knowledge and future perspectives

Rheumatic heart disease (RHD) is a cardiovascular disease caused by an autoimmune response to group A Streptococcus (GAS) infection resulting in the damage of heart valves. RHD is the most commonly acquired heart disease among children and young adults with a global burden of over 40 million cases accounting for 306,000 deaths annually. Inflammation in the heart valves caused due to molecular mimicry between the GAS antigens and host cardiac proteins is facilitated by cytokines, cross-reactive antibodies and CD4⁺ T cells. The complex interaction between genetic and environmental factors linked with erratic events leads to the loss of immunological tolerance and autoimmunity in RHD. Despite extensive research on the etiopathogenesis of RHD, the precise mechanism underpinning the initiation of acute rheumatic fever (ARF) to the progression of RHD still remains elusive. Mounting evidences support the contribution of the human microbiome in the development of several immune-mediated diseases including rheumatoid arthritis, juvenile idiopathic arthritis, Kawasaki disease, inflammatory bowel disease and type 1 diabetes. The microbiome and their metabolites could play a crucial role in the integrity of the epithelial barrier, development of the immune system, inflammation and differentiation of T cell subsets. Consequently, microbiome dysbiosis might result in autoimmunity by molecular mimicry, epitope spreading and bystander activation. This review discusses various aspects of the interaction between the microbiome and the immune system in order to reveal causative links relating dysbiosis and autoimmune diseases with special emphasis on RHD.

Genetic polymorphisms of TNF-α, IL-6, and IL-10 in female elderly patients with chronic temporomandibular disorder pain

AIM

To verify the association of the TNF-α, IL-6, and IL-10 polymorphisms with chronic temporomandibular disorder pain development in female elderly patients.

METHODS

Participants were evaluated according to Diagnostic Criteria for Temporomandibular Disorders. The genomic DNA was extracted from blood according to the Salting Out method followed by a quantification using the NanoDrop spectrophotometer. The -308G/A TNF-α polymorphism analysis was performed by the polymerase chain reaction-restriction fragment length polymorphism technique, the determination of -174G/C IL-6 polymorphism was performed by polymerase chain reaction, and the evaluation of the -1082A/G IL-10 polymorphism was carried out by polymerase chain reaction- allele-specific amplification. Data were analyzed using the BioEstat 5.3 software.

RESULTS

The -308G/A TNF-α polymorphism showed a significant difference when genotypes of cases with chronic temporomandibular disorder pain and controls were compared (p = .025). There was a lack of association regarding the -174G/C IL-6 polymorphism (p = .286) however, a positive association between the -1082A/G IL-10 polymorphism with chronic temporomandibular disorder was observed (p = .020).

CONCLUSION

The analyzed data of elderly subjects support the possible involvement of the GA genotype of the -308G/A TNF-α and the AA genotype of the -1082A/G IL-10 polymorphisms in the pathogenesis of chronic temporomandibular disorder pain.

Cytokine gene functional polymorphisms and phenotypic expression as predictors of evolution from latent to clinical rheumatic heart disease

INTRODUCTION

Inflammation associated with rheumatic heart disease (RHD) is influenced by gene polymorphisms and inflammatory cytokines. There are currently no immunologic and genetic markers to discriminate latent versus clinical patients, critical to predict disease evolution. Employing machine-learning, we searched for predictors that could discriminate latent versus clinical RHD, and eventually identify latent patients that may progress to clinical disease.

METHODS

A total of 212 individuals were included, 77 with latent, 100 with clinical RHD, and 35 healthy controls. Circulating levels of 27 soluble factors were evaluated using Bio-Plex ProTM® Human Cytokine Standard 27-plex assay. Gene polymorphism analyses were performed using RT-PCR for the following genes: IL2, IL4, IL6, IL10, IL17A, TNF and IL23.

RESULTS

Serum levels of all cytokines were higher in clinical as compared to latent RHD patients, and in those groups than in controls. IL-4, IL-8, IL-1RA, IL-9, CCL5 and PDGF emerged in the final multivariate model as predictive factors for clinical, compared with latent RHD. IL-4, IL-8 and IL1RA had the greater power to predict clinical RHD. In univariate analysis, polymorphisms in IL2 and IL4 were associated with clinical RHD and in the logistic analysis, IL6 (GG + CG), IL10 (CT + TT), IL2 (CA + AA) and IL4 (CC) genotypes were associated with RHD.

CONCLUSION

Despite higher levels of all cytokines in clinical RHD patients, IL-4, IL-8 and IL-1RA were the best predictors of clinical disease. An association of polymorphisms in IL2, IL4, IL6 and IL10 genes and clinical RHD was observed. Gene polymorphism and phenotypic expression of IL-4 accurately discriminate latent versus clinical RHD, potentially instructing clinical management.

Genetic variants in rheumatic fever and rheumatic heart disease

Genetic association studies in rheumatic heart disease (RHD) have the potential to contribute toward our understanding of the pathogenetic mechanism, and may shed light on controversies about RHD etiology. Furthermore, genetic association studies may uncover biomarkers that can be used to identify susceptible individuals, and contribute toward developing vaccine and novel therapeutic targets. Genetic predisposition to rheumatic fever and RHD has been hypothesized by findings from familial studies and observed associations between genes located in the human leukocyte antigens on chromosome 6p21.3 and elsewhere in the genome. We sought to summarize, from published Genetic association studies in RHD, evidence on genetic variants implicated in RHD susceptibility. Using HuGENet™ systematic review methods, we evaluated 66 studies reporting on 42 genes. Existing meta-analyses of candidate gene studies suggest that TGF-β1 [rs1800469], and IL-1β [rs2853550] single nucleotide polymorphisms (SNPs) contribute to susceptibility to RHD, whereas the TNF-α [rs1800629 and rs361525], TGF-β1 [rs1800470 and rs4803457], IL-6 [rs1800795], IL-10 [rs1800896] were not associated with RHD. However, candidate gene studies in RF/RHD are relatively small, thus lacking statistical power to identify reliable and reproducible findings, emphasizing the need for large-scale multicenter studies with different populations.