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Genome-wide analysis of single-locus and epistasis single-nucleotide polymorphism effects on anti-cyclic citrullinated peptide as a measure of rheumatoid arthritis.

Ma L, Dvorkin D, Garbe JR, Da Y - BMC Proc (2007)

Bottom Line: Three single-locus effects of two SNPs were significant (p < 10-4).A total of ten epistasis effects of eight pairs of SNPs on 11 autosomes and the X chromosome had significant epistasis effects (p < 10-7).The results indicate that the genetic factors underlying anti-CCP may include single-gene action and gene interactions and that the gene-interaction mechanism underlying anti-CCP could be a complex mechanism involving pairwise epistasis effects and multiple SNPs.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Animal Science, University of Minnesota, 1364 Eckles Avenue, St, Paul, Minnesota 55108, USA. maxxx131@umn.edu

ABSTRACT
The goal of this study was to identify single-locus and epistasis effects of SNP markers on anti-cyclic citrullinated peptide (anti-CCP) that is associated with rheumatoid arthritis, using the North American Rheumatoid Arthritis Consortium data. A square root transformation of the phenotypic values of anti-CCP with sex, smoking status, and a selected subset of 20 single-nucleotide polymorphism (SNP) markers in the model achieved residual normality (p > 0.05). Three single-locus effects of two SNPs were significant (p < 10-4). The epistasis analysis tested five effects of each pair of SNPs, the two-locus interaction, additive x additive, additive x dominance, dominance x additive, and dominance x dominance effects. A total of ten epistasis effects of eight pairs of SNPs on 11 autosomes and the X chromosome had significant epistasis effects (p < 10-7). Three of these epistasis effects reached significance levels of p < 10-8, p < 10-9, and p < 10-10, respectively. Two potential SNP epistasis networks were identified. The results indicate that the genetic factors underlying anti-CCP may include single-gene action and gene interactions and that the gene-interaction mechanism underlying anti-CCP could be a complex mechanism involving pairwise epistasis effects and multiple SNPs.

No MeSH data available.


Related in: MedlinePlus

Histograms of anti-CCP distributions. A-D significantly deviated from the normal distribution (p < 0.01). The deviations from normal distribution were insignificant in E (p > 0.15) and F (p > 0.05). A, Phenotypic distribution of anti-CCP values; B, residual distribution of anti-CCP values under the model with sex and smoking status as the fixed effects; C, residual distribution of anti-CCP values under the model with sex, smoking status, and all 37 SNPs with significant single-locus and epistasis effects as the fixed effects; D, residual distribution of the square root transformed anti-CCP values under the model with sex and smoking status as the fixed effects; E, residual distribution of the square root transformed anti-CCP values under the model with sex, smoking status, and all 41 SNPs with significant single-locus and epistasis effects as the fixed effects; F, residual distribution of the square root transformed anti-CCP values under the model with sex, smoking status, and a minimal subset of 20 SNPs from the 41 SNPs in E, to achieve normality.
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Figure 1: Histograms of anti-CCP distributions. A-D significantly deviated from the normal distribution (p < 0.01). The deviations from normal distribution were insignificant in E (p > 0.15) and F (p > 0.05). A, Phenotypic distribution of anti-CCP values; B, residual distribution of anti-CCP values under the model with sex and smoking status as the fixed effects; C, residual distribution of anti-CCP values under the model with sex, smoking status, and all 37 SNPs with significant single-locus and epistasis effects as the fixed effects; D, residual distribution of the square root transformed anti-CCP values under the model with sex and smoking status as the fixed effects; E, residual distribution of the square root transformed anti-CCP values under the model with sex, smoking status, and all 41 SNPs with significant single-locus and epistasis effects as the fixed effects; F, residual distribution of the square root transformed anti-CCP values under the model with sex, smoking status, and a minimal subset of 20 SNPs from the 41 SNPs in E, to achieve normality.

Mentions: The NARAC data set was edited by requiring each individual to have SNP genotypes on the 5700 SNPs and anti-CCP record, and 1466 individuals satisfied this criterion. The anti-CCP values significantly deviated from normal distribution with p < 0.01 (Fig. 1A), according to the Shapiro-Wilk, Kolmogorov-Smirnov, Cramer-von Mises, and Anderson-Darling tests offered by SAS UNIVARIATE PROCEDURE [3]. Because the residual normal distribution, not the phenotypic normal distribution, is required for the statistical tests in this article, a statistical model that achieves residual normality was found using the procedure leading to Figures 1B–1F. The untransformed anti-CCP did not achieve residual normality (p < 0.01; Fig. 1B–1C). The Box-Cox transformation [4] for a range of λ values and the square root transformation of anti-CCP were evaluated to find an optimal transformation that has the minimal sum of squares under the model for Figure 1B and improves the residual normality. None of the transformations achieved residual normality (p < 0.01), but the square root transformation was found to have minimal residual sum of squares. The residual distribution under this transformation is shown in Figure 1D. For the model used in Figure 1D, a total of 41 SNPs were found to have significant single-locus and epistasis effects with the same significance level as the SNPs for Figure 1C. Adding all the 41 SNPs in the model for Figure 1D achieved a near-perfect residual normality (p > 0.15; Fig. 1E). To reduce the model degrees of freedom or increase the residual degrees of freedom, step-wise elimination of SNPs from the full model for Figure 1E was conducted to find the minimal set of SNPs that had 20 SNPs (Table 1) and still achieved residual normality for the transformed data (p > 0.05; Fig. 1F). In the model for Figure 1F, each SNP with a single-locus effect was fitted in model as a locus with three genotypes while each pair of SNPs were fitted in the model as a genetic factor with nine (3 × 3) genotypes. Each SNP or SNP pair in this subset was re-tested by treating the other SNPs in the set as fixed effects (in addition to sex and smoking status). For all SNPs not in this subset, the SNP effects were tested based on the model for Figure 1F. The model for testing single-locus effects was


Genome-wide analysis of single-locus and epistasis single-nucleotide polymorphism effects on anti-cyclic citrullinated peptide as a measure of rheumatoid arthritis.

Ma L, Dvorkin D, Garbe JR, Da Y - BMC Proc (2007)

Histograms of anti-CCP distributions. A-D significantly deviated from the normal distribution (p < 0.01). The deviations from normal distribution were insignificant in E (p > 0.15) and F (p > 0.05). A, Phenotypic distribution of anti-CCP values; B, residual distribution of anti-CCP values under the model with sex and smoking status as the fixed effects; C, residual distribution of anti-CCP values under the model with sex, smoking status, and all 37 SNPs with significant single-locus and epistasis effects as the fixed effects; D, residual distribution of the square root transformed anti-CCP values under the model with sex and smoking status as the fixed effects; E, residual distribution of the square root transformed anti-CCP values under the model with sex, smoking status, and all 41 SNPs with significant single-locus and epistasis effects as the fixed effects; F, residual distribution of the square root transformed anti-CCP values under the model with sex, smoking status, and a minimal subset of 20 SNPs from the 41 SNPs in E, to achieve normality.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2367477&req=5

Figure 1: Histograms of anti-CCP distributions. A-D significantly deviated from the normal distribution (p < 0.01). The deviations from normal distribution were insignificant in E (p > 0.15) and F (p > 0.05). A, Phenotypic distribution of anti-CCP values; B, residual distribution of anti-CCP values under the model with sex and smoking status as the fixed effects; C, residual distribution of anti-CCP values under the model with sex, smoking status, and all 37 SNPs with significant single-locus and epistasis effects as the fixed effects; D, residual distribution of the square root transformed anti-CCP values under the model with sex and smoking status as the fixed effects; E, residual distribution of the square root transformed anti-CCP values under the model with sex, smoking status, and all 41 SNPs with significant single-locus and epistasis effects as the fixed effects; F, residual distribution of the square root transformed anti-CCP values under the model with sex, smoking status, and a minimal subset of 20 SNPs from the 41 SNPs in E, to achieve normality.
Mentions: The NARAC data set was edited by requiring each individual to have SNP genotypes on the 5700 SNPs and anti-CCP record, and 1466 individuals satisfied this criterion. The anti-CCP values significantly deviated from normal distribution with p < 0.01 (Fig. 1A), according to the Shapiro-Wilk, Kolmogorov-Smirnov, Cramer-von Mises, and Anderson-Darling tests offered by SAS UNIVARIATE PROCEDURE [3]. Because the residual normal distribution, not the phenotypic normal distribution, is required for the statistical tests in this article, a statistical model that achieves residual normality was found using the procedure leading to Figures 1B–1F. The untransformed anti-CCP did not achieve residual normality (p < 0.01; Fig. 1B–1C). The Box-Cox transformation [4] for a range of λ values and the square root transformation of anti-CCP were evaluated to find an optimal transformation that has the minimal sum of squares under the model for Figure 1B and improves the residual normality. None of the transformations achieved residual normality (p < 0.01), but the square root transformation was found to have minimal residual sum of squares. The residual distribution under this transformation is shown in Figure 1D. For the model used in Figure 1D, a total of 41 SNPs were found to have significant single-locus and epistasis effects with the same significance level as the SNPs for Figure 1C. Adding all the 41 SNPs in the model for Figure 1D achieved a near-perfect residual normality (p > 0.15; Fig. 1E). To reduce the model degrees of freedom or increase the residual degrees of freedom, step-wise elimination of SNPs from the full model for Figure 1E was conducted to find the minimal set of SNPs that had 20 SNPs (Table 1) and still achieved residual normality for the transformed data (p > 0.05; Fig. 1F). In the model for Figure 1F, each SNP with a single-locus effect was fitted in model as a locus with three genotypes while each pair of SNPs were fitted in the model as a genetic factor with nine (3 × 3) genotypes. Each SNP or SNP pair in this subset was re-tested by treating the other SNPs in the set as fixed effects (in addition to sex and smoking status). For all SNPs not in this subset, the SNP effects were tested based on the model for Figure 1F. The model for testing single-locus effects was

Bottom Line: Three single-locus effects of two SNPs were significant (p < 10-4).A total of ten epistasis effects of eight pairs of SNPs on 11 autosomes and the X chromosome had significant epistasis effects (p < 10-7).The results indicate that the genetic factors underlying anti-CCP may include single-gene action and gene interactions and that the gene-interaction mechanism underlying anti-CCP could be a complex mechanism involving pairwise epistasis effects and multiple SNPs.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Animal Science, University of Minnesota, 1364 Eckles Avenue, St, Paul, Minnesota 55108, USA. maxxx131@umn.edu

ABSTRACT
The goal of this study was to identify single-locus and epistasis effects of SNP markers on anti-cyclic citrullinated peptide (anti-CCP) that is associated with rheumatoid arthritis, using the North American Rheumatoid Arthritis Consortium data. A square root transformation of the phenotypic values of anti-CCP with sex, smoking status, and a selected subset of 20 single-nucleotide polymorphism (SNP) markers in the model achieved residual normality (p > 0.05). Three single-locus effects of two SNPs were significant (p < 10-4). The epistasis analysis tested five effects of each pair of SNPs, the two-locus interaction, additive x additive, additive x dominance, dominance x additive, and dominance x dominance effects. A total of ten epistasis effects of eight pairs of SNPs on 11 autosomes and the X chromosome had significant epistasis effects (p < 10-7). Three of these epistasis effects reached significance levels of p < 10-8, p < 10-9, and p < 10-10, respectively. Two potential SNP epistasis networks were identified. The results indicate that the genetic factors underlying anti-CCP may include single-gene action and gene interactions and that the gene-interaction mechanism underlying anti-CCP could be a complex mechanism involving pairwise epistasis effects and multiple SNPs.

No MeSH data available.


Related in: MedlinePlus