Although stressful events are known to trigger Graves’ disease (GD), the mechanisms involved in this process are not well understood. The NR3C1 gene, encoding for the glucocorticoid receptor (GR), presents single nucleotide polymorphisms (SNPs) that are associated with stress-related diseases. To investigate the relationship between NR3C1 SNPs, GD susceptibility, and clinical features, we studied 792 individuals, including 384 patients, among which 209 presented with Graves’ orbitopathy (GO), and 408 paired healthy controls. Stressful life events were evaluated in a subset of 59 patients and 66 controls using the IES-R self-report questionnaire. SNPs rs104893913, rs104893909, and rs104893911 appeared at low frequencies and presented similar profiles in patients and controls. However, variant forms of rs6198 were rarer in GD patients, suggesting a protective effect. Stressful events were more common in patients than controls, and were reported to have clearly occurred immediately before the onset of GD symptoms in 23 cases. However, no association was found between these events and rs6198 genotypes or GD/GO characteristics. We suggest that the NR3C1 rs6198 polymorphism may be an important protective factor against GD, but its relationship with stressful events needs further investigation.

Understanding the complex mechanisms involved in diseases caused by or related to important genetic variants has led to the development of clinically useful biomarkers. However, the increasing number of described variants makes it difficult to identify variants worthy of investigation, and poses challenges to their validation. We combined publicly available datasets and open source robust bioinformatics tools with molecular quantum chemistry methods to investigate the involvement of selectins, important molecules in the cell adhesion process that play a fundamental role in the cancer metastasis process. We applied this strategy to investigate single nucleotide variants (SNPs) in the intronic and UTR regions and missense SNPs with amino acid changes in the SELL, SELP, SELE, and SELPLG genes. We then focused on thyroid cancer, seeking these SNPs potential to identify biomarkers for susceptibility, diagnosis, prognosis, and therapeutic targets. We demonstrated that SELL gene polymorphisms rs2229569, rs1131498, rs4987360, rs4987301 and rs2205849; SELE gene polymorphisms rs1534904 and rs5368; rs3917777, rs2205894 and rs2205893 of SELP gene; and rs7138370, rs7300972 and rs2228315 variants of SELPLG gene may produce important alterations in the DNA structure and consequent changes in the morphology and function of the corresponding proteins. In conclusion, we developed a strategy that may save valuable time and resources in future investigations, as we were able to provide a solid foundation for the selection of selectin gene variants that may become important biomarkers and deserve further investigation in cancer patients. Large-scale clinical studies in different ethnic populations and laboratory experiments are needed to validate our results.

Selectins are responsible for the early stages of cell migration as they control cell adhesion. They make the microenvironment permissive for metastatic events by promoting the activation of other cell adhesion molecules (CAMs). We employed several robust bioinformatics tools to evaluate gene sequence; single nucleotide polymorphisms (SNPs) in intronic and UTR regions; and missense SNPs with amino acid change in L-selectin (SELL), E-selectin (SELE), P-selectin (SELP) and PSGL-1 (SELPLG). We demonstrated that gene polymorphisms rs2229569, rs1131498, rs4987360, rs4987301 and rs2205849; polymorphisms rs3917777, rs2205894 and rs2205893 of SELP gene; rs7138370, rs7300972 and rs2228315 variants of SELPLG gene; and rs1534904 and rs5368 polymorphisms of SELE gene may produce important alterations in the DNA structure and consequent alterations in the morphology and function of the corresponding proteins. These Selectin polymorphic variants deserve further investigation in cancer patients, as they may become useful clinical markers for risk determination, diagnostic and prognostic biomarkers or even targets for targeted therapies.