1) The document presents two principal component analysis (PCA)-based unsupervised feature extraction methods (VBPCAFE and CPCAFE) for analyzing gene/microRNA expression data from stressed mouse hearts to understand posttraumatic stress disorder (PTSD)-mediated heart disease. 2) In synthetic tests, unsupervised methods outperformed supervised methods when there was label noise, demonstrating robustness to mislabeling. 3) When applied to real biological gene expression data, CPCAFE identified features with expected biological relationships and terms relevant to heart disease and neurodegeneration, performing better than supervised methods.