nan values in GCTA priors

I am trying to estimate the heritability explained by genotyped SNPs from 14k individuals. The individuals are pruned for relatedness and are pan-European. I am currently not including any covariates in the analysis. I am getting the following output.


Options:
--grm-bin ../../grm/geno/X1.geno
--pheno X1.pheno
--reml
--reml-no-constrain
--thread-num 10

Note: the program will be running on 10 threads.

Reading IDs of the GRM from [../../grm/geno/X1.geno.grm.id].
14153 IDs read from [../../grm/geno/X1.geno.grm.id].
Reading the GRM from [../../grm/geno/X1.geno.grm.bin].
Reading the number of SNPs for the GRM from [../../grm/geno/X1.geno.grm.N.bin].
Pairwise genetic relationships between 14153 individuals are included from [../../grm/geno/X1.geno.grm.bin].
Reading phenotypes from [X1.pheno].
Non-missing phenotypes of 14153 individuals are included from [X1.pheno].
Assuming a disease phenotype for a case-control study:7151 cases and 7002 controls
Note: you can specify the disease prevalence by the option --prevalence so that GCTA can transform the variance explained to the underlying liability scale.
14153 individuals are in common in these files.

Performing REML analysis ... (Note: may take hours depending on sample size).
14153 observations, 1 fixed effect(s), and 2 variance component(s)(including residual variance).
Calculating prior values of variance components by EM-REML ...
Updated prior values: -nan 0.128096
logL: -inf
Running AI-REML algorithm ...
Iter. logL V(G) V(e)

Error: the X^t * V^-1 * X matrix is not invertible. Please check the covariate(s) and/or the environmental factor(s).


I am not sure what's going on here. I've tried this by setting the priors via --reml-priors. The last lines of the output were as follows:

Updated prior values: -nan 0.128096
logL: -inf
Running AI-REML algorithm ...
Iter. logL V(G) V(e)

Error: the X^t * V^-1 * X matrix is not invertible. Please check the covariate(s) and/or the environmental factor(s).

Any help will be greatly appreciated.