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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao European Journal of ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
European Journal of Internal Medicine
Article . 2010 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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A 3-factor epistatic model predicts digital ulcers in Italian scleroderma patients

Authors: Michael Mayo; Lorenzo Beretta; Maurizio Marchini; Maurizio Marchini; Raffaella Scorza; Raffaella Scorza; Francesca Cappiello; +1 Authors

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

Abstract

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

Keywords

Adult, Male, Multifactorial Inheritance, Scleroderma, Systemic, Genotype, Genes, MHC Class II, Genes, MHC Class I, Epistasis, Genetic, Middle Aged, Polymorphism, Single Nucleotide, Fingers, Italy, Cytokine; Digital ulcers; Epistasis; HLA; Petri nets; Systemic sclerosis, Skin Ulcer, Cytokines, Humans, Female, Genetic Predisposition to Disease

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Average
Average
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