TABLE 1
FROM:
Novel association suggests multiple independent QTLs within chromosome 5q21–33 region control variation in total humans IgE levels
K R Ahmadi, J S Lanchbury, P Reed, M Chiano, D Thompson, M Galley, A Line, E Lank, H J Wong, D Strachan and T D Spector
BACK TO ARTICLETable 1. Path analysis and genetic model fitting results for variation in total IgE levels
| Phenotype | Model |
2
| Df |
2
|
Df
| P |
|---|---|---|---|---|---|---|
| IgE | ACE+age | 13.43 | 7 | — | — | — |
| ADE+age | 14.93 | 7 | — | — | — | |
| ACE | 15.61 | 8 | 2.18 | 1 | 0.14 a | |
| AE | 15.61 | 9 | 0.00 | 1 | 1.00 b | |
| CE | 54.00 | 9 | 38.39 | 1 | <0.00001 b | |
| E | 175.5 | 10 | 159.89 | 1 | <0.00001 c |
a Compared to [ACE+age] model.
b Compared to [ACE] model.
c Compared to [AE] model.
The significance of age and components A, C, and D was assessed by testing the deterioration in model fit after each component was dropped from the full model. In quantitative genetic studies of human populations, the confounding effects of C and D means that they cannot both be included in the same model of twin data and as a result the full model is either the [ACE+age] or [ADE+age]. Standard hierarchic 2 tests were used to select the best fitting model. The increase in DF from the full models (ie ACE + age or ADE + age) to the nested models (i.e. ACE, AE, CE, and E) are as a result of the drop in the numbers of parameters estimated as one moves down the model hierarchy. The best fitting model is shown in bold type.
2=chi-squared goodness-of-fit statistic; Df=degrees of freedom; 
Df=(df submodel)-(df full model) 
2=(2 submodel)-(2 full model); P=probability; A=additive genetic influence; D=dominance genetic influence; C=shared environmental variance; E=unique environmental variance.
