[R] how to read association of variable in multiple outcomes using MCMCMGLMM

[Victor Chikwapulo]

Dear all,
 I am  using package MCMCglmm and I would like to request for an
assistant on  what
to look   in the output which can tell me  whether there is
significant  association among the three antibody
titers(logiga,logigm,logigg)  for example association between antibody
titers and exposure I can look at pMCMC and confidence interval if
pMCMC is less than 0.05 then  the association is significant and this
is clearly explained in  mcmcglmm course notes but for association between
outcome variables  is not clearly stated on how one can tell whether
there is significant association between the outcome variable. Please
help me, I have been looking for this answer on internet for  month
now and I tried to simulate the data just to learn the interpretation
but I could not make sense of the output.

here is the model:
m1<- MCMCglmm(cbind(logiga,logigm,logigg) ~1+trait:exposure, random =
~us(trait):ptid,
                rcov = ~idh(trait):units, family = c("gaussian",
"gaussian","gaussian"),
                data = dat, prior = pri, verbose = FALSE)


summary(m1)
Iterations = 3001:12991
 Thinning interval  = 10
 Sample size  = 1000

 DIC: 772.0578

 G-structure:  ~us(trait):ptid

                             post.mean l-95% CI u-95% CI eff.samp
traitlogiga:traitlogiga.ptid   0.26776  0.14159  0.43126    906.8
traitlogigm:traitlogiga.ptid  -0.16155 -0.26484 -0.06026   1000.0
traitlogigg:traitlogiga.ptid  -0.01804 -0.09317  0.05087    872.0
traitlogiga:traitlogigm.ptid  -0.16155 -0.26484 -0.06026   1000.0
traitlogigm:traitlogigm.ptid   0.34228  0.14773  0.54208    834.4
traitlogigg:traitlogigm.ptid   0.06099 -0.03872  0.16586    855.3
traitlogiga:traitlogigg.ptid  -0.01804 -0.09317  0.05087    872.0
traitlogigm:traitlogigg.ptid   0.06099 -0.03872  0.16586    855.3
traitlogigg:traitlogigg.ptid   0.14241  0.08026  0.23024   1000.0

 R-structure:  ~idh(trait):units

                  post.mean l-95% CI u-95% CI eff.samp
traitlogiga.units   0.09538  0.07516   0.1181     1000
traitlogigm.units   0.37488  0.28979   0.4623     1000
traitlogigg.units   0.17954  0.13917   0.2199     1126

 Location effects: cbind(logiga, logigm, logigg) ~ 1 + trait:exposure

                     post.mean l-95% CI u-95% CI eff.samp  pMCMC
(Intercept)            1.35329  1.21504  1.48696    799.8 <0.001 ***
traitlogiga:exposure   0.09773 -0.07234  0.30338   1000.0  0.322
traitlogigm:exposure   0.60556  0.26668  0.97050   1000.0 <0.001 ***
traitlogigg:exposure   0.22682 -0.01893  0.49654   1000.0  0.090 .