Carcass weight (CW), ribeye area (EMA), backfat thickness (BF), and marbling score (MS) are economically important carcass traits of Hanwoo cattle. However, significant signals detected by genome-wide association studies (GWASs) are often difficult to interpret mechanistically owing to their polygenic architecture and linkage disequilibrium (LD), which may obscure the causal genes and pathways. In this study, we defined candidate genes significantly reported in three Hanwoo carcass-trait GWASs as seeds and applied network propagation to Cytoscape–STRING protein–protein interaction (PPI) networks to (i) re-rank trait-specific candidates in a network-informed manner and (ii) propose additional connected candidates that were not directly observed in GWAS (nonseed connectors). After constructing a Bos taurus STRING network, we built trait-specific networks by including a maximum of 20 additional interactors (interactors = 20) and computed the diffusion (heat) scores and ranks. CW and EMA repeatedly prioritized growth- and skeletal/muscle development–related candidates (the PLAG1–CHCHD7 axis) among the top-ranked non-seed genes. For BF, autophagy- and insulin resistance–related candidates (BECN1 and ENPP1) were prioritized, whereas for MS, a triglyceride synthesis and lipid droplet formation candidate (GPAT4) emerged as a top-ranked non-seed gene. Overall, this approach integrates heterogeneous GWAS findings at the network level, structures trait-relevant biological pathways, and efficiently narrows down the targets for downstream validation.