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dc.contributor.authorBeretta, Lorenzo
dc.contributor.authorSantaniello, Alessandro
dc.contributor.authorMayo, Michael
dc.contributor.authorCappiello, Francesca
dc.contributor.authorMarchini, Maurizio
dc.contributor.authorScorza, Raffaella
dc.date.accessioned2010-07-05T22:15:01Z
dc.date.available2010-07-05T22:15:01Z
dc.date.issued2010
dc.identifier.citationBeretta, 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.en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/4097
dc.description.abstractBackground 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.en_NZ
dc.language.isoen
dc.publisherElsevieren_NZ
dc.subjectCytokineen_NZ
dc.subjectHLAen_NZ
dc.subjectPetri netsen_NZ
dc.subjectEpistasisen_NZ
dc.subjectSystemic sclerosisen_NZ
dc.subjectDigital ulcersen_NZ
dc.subjectMachine learning
dc.titleA 3-factor epistatic model predicts digital ulcers in Italian scleroderma patientsen_NZ
dc.typeJournal Articleen_NZ
dc.identifier.doi10.1016/j.ejim.2010.05.010en_NZ
dc.relation.isPartOfEuropean Journal of Internal Medicineen_NZ
pubs.begin-page347en_NZ
pubs.elements-id35059
pubs.end-page353en_NZ
pubs.issue4en_NZ
pubs.volume21en_NZ


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