Previous studies have suggested that exposure to ionizing radiation increases the risk of ischemic heart disease (IHD). The data from the Mayak nuclear worker cohort have indicated enhanced risk for IHD incidence. The goal of this study was to elucidate molecular mechanisms of radiation-induced IHD by integrating proteomics data with a transcriptomics study on post mortem cardiac left ventricle samples from Mayak workers categorized in four radiation dose groups (0 Gy, < 100 mGy, 100-500 mGy, > 500 mGy). The proteomics data that were newly analysed here, originated from a label-free analysis of cardiac samples. The transcriptomics analysis was performed on a subset of these samples. Stepwise linear regression analyses were used to correct the age-dependent changes in protein expression, enabling the separation of proteins, the expression of which was dependent only on the radiation dose, age or both of these factors. Importantly, the majority of the proteins showed only dose-dependent expression changes. Hierarchical clustering of the proteome and transcriptome profiles confirmed the separation of control and high-dose samples. Restrictive (separate p-values) and integrative (combined p-value) approaches were used to investigate the enrichment of biological pathways. The integrative method proved superior in the validation of the key biological pathways found in the proteomics analysis, namely PPAR signalling, TCA cycle and glycolysis/gluconeogenesis. This study presents a novel, improved, and comprehensive statistical approach of analysing biological effects on a limited number of samples.