Cardiac diseases are the most common life-threatening diseases in the world. The present study aimed to identify the common and disease-specific signatures for various cardiac diseases by using interspecies microarray sets. By meta-analysis of the datasets, we found 106 common differentially expressed genes (DEGs) between humans and mice. The common DEGs were further examined using various methods such as functional enrichment analysis, randomized network analysis, and cluster-network analysis. By analysis of 11 functional clusters, we obtained 12 highly sensitive common cardiac disease-associated genes that had never been identified before. To examine the sensitivity of the genes to the cardiac pathology, junctate-transgenic (TG) mice with cardiac hypertrophy and arrhythmias symptoms were used. The study led to the identification of eight positive genes (i.e., Synpo2l, Pros1, Crlf1, Col3a1, Frzb, Tm9sf3, Prdx4, and Ltbp2), highly upregulated in the TG mice. Cluster and network analysis showed that the cell survival and death network (cluster 7), extracellular network (cluster 9), and inflammation network (cluster 11) are cardiac disease-specific clusters. We also found that transforming growth factor-${eta}$ signaling was closely related to the common signatures and that necrosis factor-${kappa}B$ signaling was a core pathway for inflammatory dilated cardiomyopathy. Taken together, our data provide a comprehensive analysis method to identify common and disease-specific signatures.