gender(⋅) is a function mapping individual i to gender ∈ {male, female}. ηcaseControl(i) is a fixed effect representing case/control status of subject i, where caseControl(⋅) is a function mapping individual i to it's case/control status for metabolic syndrome ∈ {case, control}, γ is a fixed effect incorporating the effect of age, αbatch(i,j) is a fixed effect included to accommodate an experimental batch effect (96-well plate format), where the function batch(⋅) is a function mapping each sample to a batch (plate) ∈ {1,2,3}. The κI are independently Gaussian distributed with mean zero and variance σ2 κ, for subject i representing inter individual variability. εij is the residual error term incorporating technical (aliquot) variability, assumed to be independently Gaussian distributed with mean zero and variance σ2 ε. The model was fitted in R, using the lme4 package[57] and the lmer() function, using maximum-likelihood. A likelihood ratio test was applied to assess the significance of the SNP effect (β), which is the parameter of main interest in the eQTL analysis. The p-value of the SNP effect in each eQTL model was calculated using a likelihood ratio (LR) test with the D = −2*log(LR) as the test statistic, which can be approximated by a
