Meta Analysis of SNPxEnvironment Interaction
Introduction
The meta-analysis of SNP-Environment interaction regression models is possible by jointly meta-analyzing and testing the SNP and SNPxE beta coefficients from an interaction regression model:
The joint meta-analysis:
- produces summary estimates of β2 and β3
- produces the estimated covariance matrix of and
- computes a test statistics for the null hypothesis: β2=0 and β3=0
- computes a test of homogeneity of the regression slopes
The joint meta-analysis method has been implemented in METAL available from http://www.sph.umich.edu/csg/abecasis/Metal (Metal Documentation). Individual studies can obtain the required beta and covariance estimates for interaction regression models using QUICKTEST version 0.95 and later (http://toby.freeshell.org/software/quicktest/) and ProbABEL version 0.1-3 and later (http://mga.bionet.nsc.ru/~yurii/ABEL/GenABEL/).
Implementation
The joint meta-analysis is executed through the SCHEME INTERACTION command. The following commands must be used for each data file:
MARKERLABEL [LABEL]
ALLELELABELS [LABEL1 LABEL2]
EFFECTLABEL [LABEL]
STDERRLABEL [LABEL]
INTEFFECTLABEL [LABEL]
INTSTDERRLABEL [LABEL]
INTCOVLABEL [LABEL]
If MINMAXFREQUENCY ON is used, FREQLABEL must be specified. If AVERAGEFREQUENCY ON is used, in addition to FREQLABEL, WEIGHTLABEL also must be specified to calculate the average frequencies of alleles. Using the sample size as the weight to calculate average allele frequency is strongly suggested. In this case, frequency results in the output will be the same as frequency results from SCHEME SAMPLESIZE.
Two columns of directions will appear in the output of SCHEME INTERACTION, one for the direction of the main effect, one for the direction of the interaction term.
The output columns are:
Effect - Summarized estimate of the SNP beta coefficient
StdErr - Estimated standard error of the SNP beta coefficient
IntEffect - Summarized estimate of the SNPxE beta coefficient
IntStdErr - Estimated standard error of the SNPxE beta coefficient
IntCov - Estimated covariance between the SNP beta coefficient and the SNPxE beta coefficient
ChiSq2df - Joint test of the SNP beta coefficient and SNPxE beta coefficient
P-value - P-value of ChiSq2df
Direction - Study-specific direction of the SNP beta-coefficient
DirectionInt - Study-specific direction of the SNPxE beta-coefficient
HetChiSq - Heterogeneity test statistic
HetDf - Heterogeneity test statistic degrees of freedom
HetPVal - Heterogeneity p-value
If ANALYZE HETEROGENEITY is specified, the heterogeneity test statistic, degrees of freedom and p-value will be produced in the output columns: HetChiSq, HetDf and HetPVal.
The command, GENOMICCONTROL ON, adjusts the test statistics within each sample by λGC, which is either pre-specified or calculated.
For sample i, the Wald test statistic for each SNP is calculated to test the joint significance of βSNP,i and βSNPxE,i:
Under the null hypothesis, these Wi's follow a chi-square distribution of 2 df. The median statistic from this distribution is 1.386294, so
for this sample.
Example
CUSTOMVARIABLE TotalSampleSize LABEL TotalSampleSize as N SCHEME INTERACTION SEPARATOR TAB MARKER SNP ALLELE EFFECT_ALLELE NON_EFFECT_ALLELE EFFECT BETA STDERR SE INTEFFECT BETA_INT INTSTDERR SE_INT INTCOV COV WEIGHT N PROCESS results1.txt PROCESS results2.txt PROCESS results3.txt PROCESS results4.txt PROCESS results5.txt OUTFILE jointmeta .txt ANALYZE OUTFILE jointmeta_het .txt ANALYZE HETEROGENEITY QUIT