In the emerging Systems Medicine field, the study of aging is re-evaluated and contextualized through the combination of ‘omics’ investigations (i.e. transcriptomic, proteomic, metabolomics, fluxomic). In particular, heart aging is a highly complex process in terms of molecular changes and the role of microRNAs (miRNAs) as key gene regulators has recently arisen. Towards this orientation, we describe a three-step methodological framework for designating markers of heart aging at the level of modules by integrating proteome and heart-specific transcriptome information in the mouse model. First, a Multilayer Large Scale Omics Network (MLSON) is constructed integrating two types of nodes (mRNAs and miRNAs) and three types of relations (mRNA-mRNA, miRNA-mRNA and miRNA-miRNA). Secondly, two adapted weighting schemes were designed and applied on MLSON, based either on mRNA or miRNA expression profiles, with the scope to pinpoint the significantly altered relations due to aging factor. Finally, an efficient module-detecting algorithm, namely Detect Module from Seed Protein (DMSP), is recruited so as to identify multilayer modular markers discriminative of the two states (young/old). Our large scale integromics approach is an enabling step towards elucidating heart longevity mechanisms at multiple levels. The identified modules provide novel biological evidence for the interference and synergistic effect of miRNAs in heart aging process.