Hi all,

I was wondering if you could help me to understand limma linear regression output for continuous variables.

I got result for epic array methylation data and eGFR association in this format;

                 logFC       AveExpr.    t         P.Value  adj.P.Val   B
cg03546163  0.41018776  -0.8013218  7.85104192  1.13E-12    8.65E-07    12.3051291
cg17944885  -0.4884859  2.31974279  -5.7319645  6.33E-08    0.02431349  5.15237109

Could you please help me to understand what is difference between B, logFC, t, and AveExpr. and what are more important output need to consider to for eGFR and CpG association here?

I have used this below model at adjust for covariates;

#model matrix

var<-model.matrix(~logeGFR + as.factor(Gender) + Age +CD8T +CD4T +NK + Bcell +Mono ,data=targets2)

Thanks again for your all help. Please share any more documents or papers that can help to understand it more.

Many thanks

If you are interpreting a continuous covariate, the value is the change in methylation for each unit increase in the covariate. In other words, for cg03546163, you have an increase in methylation of 0.41 for every unit increase in logeGPR.

Assuming that 'logeGPR' means log_2(eGPR) (it should!), every unit increase in logeGPR represents a doubling of eGPR exposure (or whatever eGPR is). Also, assuming that you are using M-values for the analysis (again, you should!), those values are also log_2 variates, so to interpret in the context of your experiment, note that 2^0.41 is 1.33, so you could interpret that coefficient to mean that the methylation at that site increases about 33% for every doubling of eGPR exposure.