1
Supplementary Table 1. Logistic regression analyses in lupus nephritis.
A
Modela / Predictor variableb / P-valuec / Logistic OR(95% C.I.) / Model c2 / df / Model P-valued
Simple / FCGR3B / 0.001 / 0.47 (0.29-0.74) / 13.5 / 3 / 0.004
B
Modela / Predictor variableb / P-valuec / Logistic OR(95% C.I.) / Model c2 / df / Model P-valued
Sequential / I / FCGR3B / < 0.001 / 0.42 (0.25-0.70) / 13.4 / 3 / 0.004
II / FCGR3B / 0.001 / 0.41 (0.25-0.70) / 2.83 / 2 / 0.243
FCGR2A-G548A / 0.25
III / FCGR3B / 0.001 / 0.41 (0.24-0.70) / 6.91 / 2 / 0.032
FCGR2A-G548A / 0.31
FCGR3A-T559G / 0.037
a In the simple logistic regression model (N=204), lupus nephritis was regressed on FCGR3B gene copy number only, and odds ratios (OR) and 95% C.I. were calculated. In the sequential logistic regression model, carried out in all subjects for whom complete genotyping and copy number was available (N=169), lupus nephritis was initially regressed on FCGR3B whereas FCGR2A-G548A and FCGR3A-T559G predictors were consecutively added to the model. All P-values were calculated after adjustment for age and sex. b FCGR2A-G548A and FCGR3A-T559G genotypes were coded as categorical variables, and the reference category was the most frequent (homozygous) genotype group. The significance for the predictor variablesc and for each modeld is reported. A logistic regression model for interactions between FCGR3B gene copy number and FCGR2A-G548A and FCGR3A-T559G genotypes was also tested but showed no statistically significant results.