Nothing in NLMIXED is as simple as it is in GLIMMIX. However, the NLMIXED documentation provides examples of models with covariates. See e.g. SAS/STAT(R) 9.2 User's Guide, Second Edition where they give this code for a model with several covariates:
proc nlmixed data=inhaler corr ecorr;
parms b0=0 b1=0 b2=0 b3=0 sd=1 i1=1 i2=1;
bounds i1 > 0, i2 > 0;
eta = b0 + b1*group + b2*time + b3*gt + u;
if (clarity=1) then p = probnorm(-eta);
else if (clarity=2) then
p = probnorm(i1-eta) - probnorm(-eta);
else if (clarity=3) then
p = probnorm(i1+i2-eta) - probnorm(i1-eta);
else p = 1 - probnorm(i1+i2-eta);
if (p > 1e-8) then ll = log(p);
else ll = -1e100;
model clarity ~ general(ll);
random u ~ normal(0,sd*sd) subject=sub;
replicate freq;
estimate 'thresh2' i1;
estimate 'thresh3' i1 + i2;
estimate 'icc' sd*sd/(1+sd*sd);
run;