TY - JOUR
T1 - Interleukin-1 gene complex single nucleotide polymorphisms in systemic sclerosis
T2 - A further step ahead
AU - Beretta, Lorenzo
AU - Cappiello, Francesca
AU - Moore, Jason H.
AU - Scorza, Raffaella
PY - 2008/3
Y1 - 2008/3
N2 - Gene-gene and gene-environment interactions are difficult to detect by traditional parametric computational approaches. Novel nonparametric and model-free strategies, such as the multifactor dimensionality reduction (MDR) algorithm, are thus emerging as practical and feasible methods of analysis to model high-order epistatic interactions, integrating and complementing traditional logistic approaches. With traditional methods of analysis we showed that the interleukin-1β (IL-1β) C+3962T single nucleotide polymorphism (SNP), along with the Sc70 antibody and the diffuse cutaneous subset of systemic sclerosis, are important risk factors for the development of a severe ventilatory restriction in patients with systemic sclerosis (SSc); however the interactions among these and other genetic and environmental attributes were difficult to model. On the contrary, the MDR analysis detected significant two- or three-way interactions in the presence of nonlinearity. The best model identified by the multifactor dimensionality reduction algorithm included the antibody subset, the IL-1β C-511T and the interferon-γ AUTR5644T SNPs, with a testing accuracy of 85% (p <0.001) and a cross-validation consistency of 10/10. This model outperformed any one- to-three-way model constructed by considering the three factors with main independent effects identified by traditional computational approaches. Epistatic interactions among IL-1 gene complex SNPs and clinical or environmental factors are more important than the singe attributes in the development of severe ventilatory restriction in SSc patients.
AB - Gene-gene and gene-environment interactions are difficult to detect by traditional parametric computational approaches. Novel nonparametric and model-free strategies, such as the multifactor dimensionality reduction (MDR) algorithm, are thus emerging as practical and feasible methods of analysis to model high-order epistatic interactions, integrating and complementing traditional logistic approaches. With traditional methods of analysis we showed that the interleukin-1β (IL-1β) C+3962T single nucleotide polymorphism (SNP), along with the Sc70 antibody and the diffuse cutaneous subset of systemic sclerosis, are important risk factors for the development of a severe ventilatory restriction in patients with systemic sclerosis (SSc); however the interactions among these and other genetic and environmental attributes were difficult to model. On the contrary, the MDR analysis detected significant two- or three-way interactions in the presence of nonlinearity. The best model identified by the multifactor dimensionality reduction algorithm included the antibody subset, the IL-1β C-511T and the interferon-γ AUTR5644T SNPs, with a testing accuracy of 85% (p <0.001) and a cross-validation consistency of 10/10. This model outperformed any one- to-three-way model constructed by considering the three factors with main independent effects identified by traditional computational approaches. Epistatic interactions among IL-1 gene complex SNPs and clinical or environmental factors are more important than the singe attributes in the development of severe ventilatory restriction in SSc patients.
KW - Epistasis
KW - Lung fibrosis
KW - Single nucleotide polymorphism
KW - Systemic sclerosis
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U2 - 10.1016/j.humimm.2007.12.006
DO - 10.1016/j.humimm.2007.12.006
M3 - Article
C2 - 18396211
AN - SCOPUS:41549104833
VL - 69
SP - 187
EP - 192
JO - Human Immunology
JF - Human Immunology
SN - 0198-8859
IS - 3
ER -