Gene polymorphisms of pro-inflammatory cytokines may affect the risk of Graves' disease: a meta-analysis

Unraveling susceptibility genes: A contemporary overview of autoimmune thyroid diseases

Autoimmune thyroid diseases (AITDs), including Graves' disease and Hashimoto's thyroiditis, are organ-specific autoimmune disorders characterized by conditions including goiter, autoimmune thyroiditis, hyperthyroidism, and hypothyroidism, which represent the most severe clinical manifestations of AITDs. The prevalence of autoimmune thyroid disorders is on the rise, influenced by increased environmental factors and changes in modern lifestyles. Understanding the pathophysiology of AITDs is crucial for identifying key factors that affect the disease's onset, progression, and recurrence, thereby laying a solid foundation for precise diagnosis and treatment. The development of AITDs involves a complex interplay of environmental influences, immune dysfunctions, and genetic predispositions. Genetic predispositions, in particular, are significant, with numerous genes identified as being linked to AITDs. This article focuses on examining the genes vulnerable to AITDs to deepen our understanding of the relevant genetic contributors, ultimately facilitating the development of effective prevention and treatment methods.

Possible molecular exploration of herbal pair Haizao-Kunbu in the treatment of Graves' disease by network pharmacology, molecular docking, and molecular dynamic analysis

Objective

To promote the development and therapeutic application of new medications, it is crucial to conduct a thorough investigation into the mechanism by which the traditional Chinese herb pair of Haizao-Kunbu (HK) treats Graves' disease (GD).

Materials and methods

Chemical ingredients of HK, putative target genes, and GD-associated genes were retrieved from online public databases. Using Cytoscape 3.9.1, a compound-gene target network was established to explore the association between prosperous ingredients and targets. STRING, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathway analyses visualized core targets and disease pathways. Additionally, we conducted a refined analysis of the binding interactions between active ingredients and their respective targets. To visualize these findings, we employed precise molecular docking techniques. Furthermore, we carried out molecular dynamics simulations to gain insights into the formation of more tightly bound complexes.

Results

We found that there were nine key active ingredients in HK, which mainly acted on 21 targets. These targets primarily regulated several biological processes such as cell population proliferation, protein phosphorylation, and regulation of kinase activity, and acted on PI3K-AKT and MAPK pathways to treat GD. Analysis of the molecular interaction simulation under computer technology revealed that the key targets exhibited strong binding activity to active ingredients, and Fucosterol-AKT1 and Isofucosterol-AKT1 complexes were highly stable in humans.

Conclusion

This study demonstrates that HK exerts therapeutic effects on GD in a multi-component, multi-target, and multi-pathway manner by regulating cell proliferation, differentiation, inflammation, and immunomodulatory-related targets. This study provides a theoretical foundation for further investigation into GD.

Detection of association of IL1β, IL4R, and IL6 gene polymorphisms with cervical cancer in the Bangladeshi women by tetra-primer ARMS-PCR method

BACKGROUND

Cervical cancer (CC) is the main cause of cancer-related deaths among women in developing countries. It is the second leading female malignancy in Bangladesh in terms of incidence and mortality. Our present study aimed to investigate the association of IL1β (rs16944), IL4R (rs1801275), and IL6 (rs1800797) gene polymorphisms with the susceptibility of cervical cancer.

MATERIALS AND METHODS

This case-control study was conducted on 252 cervical cancer patients and 228 healthy volunteers, using tetra-primer amplification refractory mutation system-polymerase chain reaction (ARMS-PCR).

RESULTS

In the case of rs16944 polymorphism, GG genotype (OR = 2.10, 95%CI = 1.24-3.56), dominant model (OR = 1.71, 95% CI = 1.11-2.63), recessive model (OR = 1.54, 95% CI = 1.01-2.35), and G allele (OR = 1.30, 95% CI = 1.005-1.68) were significantly associated with increased cervical cancer risk. Among these, GG genotype and dominant model remained significant after the Bonferroni correction (p < 0.017). For rs1801275 polymorphism, GG genotype (OR = 2.66, 95% CI = 1.49-4.75), dominant model (OR = 1.49, 95% CI = 1.04-2.14), recessive model (OR = 2.45, 95% CI = 1.40-4.27), and G allele (OR = 1.59, 95% CI = 1.21-2.10) significantly elevated the risk of cervical cancer but significance did not exist for dominant model after the Bonferroni correction. rs1800797 variant showed significantly increased risk in all genetic models including, AG genotype (OR = 8.13, 95% CI = 5.27-12.55), AA genotype (OR = 9.86, 95% CI = 2.76-35.21), dominant model (OR = 8.25, 95% CI = 5.40-12.60), recessive model (OR = 4.41, 95% CI = 1.25-15.56), and A allele (OR = 4.99, 95% CI = 3.49-7.13) and the significances were consistent with the Bonferroni correction except recessive model. Haplotyping analysis indicates that GAA (p = 5.15x10^-5) and GAG haplotypes (p = 4.72x10^-9) significantly decreased the risk of CC, whereas AAA (p = 3.89x10-9), AAG (p = 0.0003), AGA (p = 3.98x10-5) and AGG haplotypes (p = 0.002) significantly increased the risk of CC. The IL1β mRNA level was up-regulated, which was associated with poor prognosis in silico.

CONCLUSION

Our results conclude that rs16944 (IL1β), rs1801275 (IL4R), and rs1800797 (IL6) polymorphisms are associated with cervical cancer in Bangladeshi women.