R correlation analysis: trying to reproduce a ggcorrplot with a subset of variables vs a different subset, using ggcorrplot2 instead

Question

I am trying to make a correlation plot with a subset of variables versus a different subset.

Using the mtcars data I do the following using ggcorrplot:

data(mtcars)
corrtest <- psych::corr.test(mtcars[,1:7], adjust="none")
all_matrix <- corrtest$r
all_pmat <- corrtest$p

pheno_markers <- names(mtcars)[1:4]
serol_markers <- names(mtcars)[5:7]
sub_matrix <- all_matrix[pheno_markers, serol_markers]
sub_pmat <- all_pmat[pheno_markers, serol_markers]

grDevices::pdf(file="heat_duo.pdf", height=4, width=4)
print(
  ggcorrplot::ggcorrplot(sub_matrix, p.mat=sub_pmat, method="circle")
)
grDevices::dev.off()

This produces the following plot, which is good:

Now I want to reproduce the same plot with ggcorrplot2 instead, cause it allows me to overlay significance values of the comparisons as ***. I use this package usually with no problem, but I do not seem to get this case right; it seems it can only deal with symmetrical matrices with colnames == rownames...

I tried the following:

grDevices::pdf(file="heat_duo2.pdf", height=4, width=4)
print(
  ggcorrplot2::ggcorrplot(sub_matrix, p.mat=sub_pmat, method="circle",
                          insig = "label_sig", sig.lvl = c(0.05, 0.01, 0.001))
)
grDevices::dev.off()

But the result is obviously wrong:

Any idea on how to deal with a case like this in ggcorrplot2 (ggcorrplot makes it so easy)?