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      A 3-factor epistatic model predicts digital ulcers in Italian scleroderma patients

      Beretta, Lorenzo; Santaniello, Alessandro; Mayo, Michael; Cappiello, Francesca; Marchini, Maurizio; Scorza, Raffaella
      DOI
       10.1016/j.ejim.2010.05.010
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      Beretta, L., Santaniello, A., Mayo, M., Cappiello, F., Marchini, M. & Scorza, R. (2010). A 3-factor epistatic model predicts digital ulcers in Italian scleroderma patients. European Journal of Internal Medicine, 21(4), 347-353.
      Permanent Research Commons link: https://hdl.handle.net/10289/4097
      Abstract
      Background

      The genetic background may predispose systemic sclerosis (SSc) patients to the development of digital ulcers (DUs).

      Methods

      Twenty-two functional cytokine single nucleotide polymorphisms (SNPs) and 3 HLA class I and II antigens were typed at the genomic level by polymerase chain reaction in 200 Italian SSc patients. Associations with DUs were sought by parametric models and with the Multifactor Dimensionality Reduction (MDR) algorithm to depict the presence of epistasis. Biological models consistent with MDR results were built by means of Petri nets to describe the metabolic significance of our findings.

      Results

      On the exploratory analysis, the diffuse cutaneous subset (dcSSc) was the only single factor statistically associated with DUs (p = 0.045, ns after Bonferroni correction). Gene–gene analysis showed that a 3-factor model comprising the IL-6 C-174G, the IL-2 G-330T SNPs and the HLA-B*3501 allele was predictive for the occurrence of DUs in our population (testing accuracy = 66.9%; p < 0.0001, permutation testing).

      Conclusion

      Biological interpretation via Petri net showed that IL-6 is a key factor in determining DUs occurrence and that this cytokines may synergise with HLA-B*3501 to determine DUs onset. Owing to the limited number of patients included in the study, future research are needed to replicate our statistical findings as well as to better determine their functional meaning.
      Date
      2010
      Type
      Journal Article
      Publisher
      Elsevier
      Collections
      • Computing and Mathematical Sciences Papers [1454]
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