I am running a PCA for quality in a water resource. I have 15 original variables. Running the PCA using Minitab, it turned out that the first PC is responsible for 99.7% of the variation. Looking at the eigenvectors, all the original values have almost the same correlation value with PC1 (about 0.25). What does that mean? Note: I tried to use the log of the data, and the results were very much the same.
It means that there is one very large component and that all the variables are roughly equal in its determination.
Since you haven't told us your variables, it's hard to say more, but something similar could happen if your 15 variables were all measurements of length of different parts of a human body. In this case, overall size of the person would be highly correlated to all the inidividual parts.