SEARCH

SEARCH BY CITATION

REFERENCES

  • 1
    Abraham DL, Varga J. Scleroderma: from cell and molecular mechanisms to disease models. Trends Immunol 2005; 26: 58795.
  • 2
    Varga J, Abraham D. Systemic sclerosis: a prototypic multisystem fibrotic disorder. J Clin Invest 2007; 117: 55767.
  • 3
    Atamas SP, White B. Cytokine regulation of pulmonary fibrosis in scleroderma. Cytokine Growth Factor Rev 2003; 14: 53750.
  • 4
    Kahaleh MB. Raynaud phenomenon and the vascular disease in scleroderma. Curr Opin Rheumatol 2004; 16: 71822.
  • 5
    Balkwill F. Cytokines and cytokine receptors. In: RoittI, BrostoffJ, MaleD, editors. Immunology. 6th ed. London: Mosby International; 2001. p. 11929.
  • 6
    Wynn TA. Fibrotic disease and the T(H)1/T(H)2 paradigm. Nat Rev Immunol 2004; 4: 58394.
  • 7
    Granel B, Chevillard C, Allanore Y, Arnaud V, Cabantous S, Marquet S, et al. Evaluation of interleukin 13 polymorphisms in systemic sclerosis. Immunogenetics 2006; 58: 6939.
  • 8
    Matsushita T, Hasegawa M, Hamaguchi Y, Takehara K, Sato S. Longitudinal analysis of serum cytokine concentrations in systemic sclerosis: association of interleukin 12 elevation with spontaneous regression of skin sclerosis. J Rheumatol 2006; 33: 27584.
  • 9
    Sato S, Hasegawa M, Takehara K. Serum levels of interleukin-6 and interleukin-10 correlate with total skin thickness score in patients with systemic sclerosis. J Dermatol Sci 2001; 27: 1406.
  • 10
    Mavalia C, Scaletti C, Romagnani P, Carossino AM, Pignone A, Emmi L, et al. Type 2 helper T-cell predominance and high CD30 expression in systemic sclerosis. Am J Pathol 1997; 151: 17518.
  • 11
    Suarez A, Castro P, Alonso R, Mozo L, Gutierrez C. Interindividual variations in constitutive interleukin-10 messenger RNA and protein levels and their association with genetic polymorphisms. Transplantation 2003; 75: 7117.
  • 12
    Pociot F, Molvig J, Wogensen L, Worsaae H, Nerup J. A TaqI polymorphism in the human interleukin-1β (IL-1β) gene correlates with IL-1β secretion in vitro. Eur J Clin Invest 1992; 22: 396402.
  • 13
    Fishman D, Faulds G, Jeffery R, Mohamed-Ali V, Yudkin JS, Humphries S, et al. The effect of novel polymorphisms in the interleukin-6 (IL-6) gene on IL-6 transcription and plasma IL-6 levels, and an association with systemic-onset juvenile chronic arthritis. J Clin Invest 1998; 102: 136976.
  • 14
    Hoffmann SC, Stanley EM, Darrin Cox E, Craighead N, DiMercurio BS, Koziol DE, et al. Association of cytokine polymorphic inheritance and in vitro cytokine production in anti-CD3/CD28-stimulated peripheral blood lymphocytes. Transplantation 2001; 72: 144450.
  • 15
    Beretta L, Santaniello A, Cappiello F, Barili M, Scorza R. No evidence for a role of the proximal IL-6 G/C -174 single nucleotide polymorphism in Italian patients with systemic sclerosis. J Cell Mol Med 2007; 11: 8968.
  • 16
    Mattuzzi S, Barbi S, Carletto A, Ravagnani V, Moore PS, Bambara LM, et al. Association of polymorphisms in the IL1B and IL2 genes with susceptibility and severity of systemic sclerosis. J Rheumatol 2007; 34: 9971004.
  • 17
    Beretta L, Bertolotti F, Cappiello F, Barili M, Masciocchi M, Toussoun K, et al. Interleukin-1 gene complex polymorphisms in systemic sclerosis patients with severe restrictive lung physiology. Hum Immunol 2007; 68: 6039.
  • 18
    Hutyrova B, Lukac J, Bosak V, Buc M, du Bois R, Petrek M. Interleukin 1α single nucleotide polymorphism associated with systemic sclerosis. J Rheumatol 2004; 31: 814.
  • 19
    Crilly A, Hamilton J, Clark CJ, Jardine A, Madhok R. Analysis of the 5' flanking region of the interleukin 10 gene in patients with systemic sclerosis. Rheumatology (Oxford) 2003; 42: 12958.
  • 20
    Beretta L, Cappiello F, Barili M, Scorza R. Proximal interleukin-10 gene polymorphisms in Italian patients with systemic sclerosis. Tissue Antigens 2007; 69: 30512.
  • 21
    Ommen ES, Winston JA, Murphy B. Medical risks in living kidney donors: absence of proof is not proof of absence. Clin J Am Soc Nephrol 2006; 1: 88595.
  • 22
    Moore JH. The ubiquitous nature of epistasis in determining susceptibility to common human diseases. Hum Hered 2003; 56: 7382.
  • 23
    Cordell HJ. Epistasis: what it means, what it doesn't mean, and statistical methods to detect it in humans. Hum Mol Genet 2002; 11: 24638.
  • 24
    Ritchie MD, White BC, Parker JS, Hahn LW, Moore JH. Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases. BMC Bioinformatics 2003; 4: 2841.
  • 25
    Martin ER, Bass MP, Gilbert JR, Pericak-Vance MA, Hauser ER. Genotype-based association test for general pedigrees: the genotype-PDT. Genet Epidemiol 2003; 25: 20313.
  • 26
    Moore JH, Gilbert JC, Tsai CT, Chiang FT, Holden T, Barney N, et al. A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. J Theor Biol 2006; 241: 25261.
  • 27
    Thornton-Wells TA, Moore JH, Haines JL. Genetics, statistics and human disease: analytical retooling for complexity. Trends Genet 2004; 20: 6407.
  • 28
    Heidema AG, Boer JM, Nagelkerke N, Mariman EC, van der A DL, Feskens EJ. The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases. BMC Genet 2006; 7: 2337.
  • 29
    Julia A, Moore J, Miquel L, Alegre C, Barcelo P, Ritchie M, et al. Identification of a two-loci epistatic interaction associated with susceptibility to rheumatoid arthritis through reverse engineering and multifactor dimensionality reduction. Genomics 2007; 90: 613.
  • 30
    Gong R, Liu Z, Li L. Epistatic effect of plasminogen activator inhibitor 1 and β-fibrinogen genes on risk of glomerular microthrombosis in lupus nephritis: interaction with environmental/clinical factors. Arthritis Rheum 2007; 56: 160817.
  • 31
    Ritchie MD, Hahn LW, Roodi N, Bailey LR, Dupont WD, Parl FF, et al. Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. Am J Hum Genet 2001; 69: 13847.
  • 32
    Xu J, Lowey J, Wiklund F, Sun J, Lindmark F, Hsu FC, et al. The interaction of four genes in the inflammation pathway significantly predicts prostate cancer risk. Cancer Epidemiol Biomarkers Prev 2005; 14: 25638.
  • 33
    Briollais L, Wang Y, Rajendram I, Onay V, Shi E, Knight J, et al. Methodological issues in detecting gene-gene interactions in breast cancer susceptibility: a population-based study in Ontario. BMC Med 2007; 5: 2236.
  • 34
    Andrew AS, Karagas MR, Nelson HH, Guarrera S, Polidoro S, Gamberini S, et al. DNA repair polymorphisms modify bladder cancer risk: a multi-factor analytic strategy. Hum Hered 2008; 65: 10518.
  • 35
    Heidema AG, Feskens EJ, Doevendans PA, Ruven HJ, van Houwelingen HC, Mariman EC, et al. Analysis of multiple SNPs in genetic association studies: comparison of three multi-locus methods to prioritize and select SNPs. Genet Epidemiol 2007; 31: 91021.
  • 36
    Subcommittee for Scleroderma Criteria of the American Rheumatism Association Diagnostic and Therapeutic Criteria Committee. Preliminary criteria for the classification of systemic sclerosis (scleroderma). Arthritis Rheum 1980; 23: 58190.
  • 37
    LeRoy EC, Black C, Fleischmajer R, Jablonska S, Krieg T, Medsger TA Jr, et al. Scleroderma (systemic sclerosis): classification, subsets and pathogenesis. J Rheumatol 1988; 15: 2025.
  • 38
    White B, Bauer EA, Goldsmith LA, Hochberg MC, Katz LM, Korn JH, et al. Guidelines for clinical trials in systemic sclerosis (scleroderma). I. Disease-modifying interventions. Arthritis Rheum 1995; 38: 35160.
  • 39
    Bayer PM, Bauerfeind S, Bienvenu J, Fabien N, Frei PC, Gilburd B, et al. Multicenter evaluation study on a new HEp2 ANA screening enzyme immune assay. J Autoimmun 1999; 13: 8993.
  • 40
    Tseng LH, Chen PJ, Lin MT, Singleton K, Martin EG, Yen AH, et al. Simultaneous genotyping of single nucleotide polymorphisms in the IL-1 gene complex by multiplex polymerase chain reaction-restriction fragment length polymorphism. J Immunol Methods 2002; 267: 1516.
  • 41
    Little RJ, Rubin DB. Statistical analysis with missing data. New York: Wiley; 2002.
  • 42
    Moore JH, White BC. Tuning relief for genome-wide genetic analysis. Lect Notes Comput Sci 2007; 4447: 16675.
  • 43
    Hahn LW, Ritchie MD, Moore JH. Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics 2003; 19: 37682.
  • 44
    Millstein J, Conti DV, Gilliland FD, Gauderman WJ. A testing framework for identifying susceptibility genes in the presence of epistasis. Am J Hum Genet 2006; 78: 1527.
  • 45
    Kleinrath T, Gassner C, Lackner P, Thurnher M, Ramoner R. Interleukin-4 promoter polymorphisms: a genetic prognostic factor for survival in metastatic renal cell carcinoma. J Clin Oncol 2007; 25: 84551.
  • 46
    Moore JH, Williams SM. Traversing the conceptual divide between biological and statistical epistasis: systems biology and a more modern synthesis. Bioessays 2005; 27: 63746.
  • 47
    Hasegawa M, Sato S, Ihn H, Takehara K. Enhanced production of interleukin-6 (IL-6), oncostatin M and soluble IL-6 receptor by cultured peripheral blood mononuclear cells from patients with systemic sclerosis. Rheumatology (Oxford) 1999; 38: 6127.
  • 48
    Gillery P, Serpier H, Polette M, Bellon G, Clavel C, Wegrowski Y, et al. Gamma-interferon inhibits extracellular matrix synthesis and remodeling in collagen lattice cultures of normal and scleroderma skin fibroblasts. Eur J Cell Biol 1992; 57: 24453.
  • 49
    Ingegnoli F, Trabattoni D, Saresella M, Fantini F, Clerici M. Distinct immune profiles characterize patients with diffuse or limited systemic sclerosis. Clin Immunol 2003; 108: 218.
  • 50
    Grassegger A, Schuler G, Hessenberger G, Walder-Hantich B, Jabkowski J, MacHeiner W, et al. Interferon-gamma in the treatment of systemic sclerosis: a randomized controlled multicentre trial. Br J Dermatol 1998; 139: 63948.
  • 51
    Seibold JR. Scleroderma and Raynaud's disease. In: HarrisED, BuddRC, FiresteinGS, GenoveseM, SergentJS, RuddysS, et al, editors. Kelley's textbook of rheumatology. 7th ed. Philadelphia: Elsevier Saunders; 2005. p. 1279306.
  • 52
    Reif DM, White BC, Moore JH. Integrated analysis of genetic, genomic and proteomic data. Expert Rev Proteomics 2004; 1: 6775.
  • 53
    Moore JH, Boczko EM, Summar ML. Connecting the dots between genes, biochemistry, and disease susceptibility: systems biology modeling in human genetics. Mol Genet Metab 2005; 84: 10411.
  • 54
    Moore JH, Hahn LW. Petri net modeling of high-order genetic systems using grammatical evolution. Biosystems 2003; 72: 17786.
  • 55
    Wacholder S, Chanock S, Garcia-Closas M, El Ghormli L, Rothman N. Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. J Natl Cancer Inst 2004; 96: 43442.
  • 56
    Hollegaard MV, Bidwell JL. Cytokine gene polymorphism in human disease: on-line databases, supplement 3. Genes Immun 2006; 7: 26976.