Background: Immune-mediated inflammatory diseases (IMIDs) involve widespread immune dysregulation and substantial therapeutic challenges, with many patients not achieving sustained responses. Advancing both mechanistic understanding and rational target selection requires molecular profiling capable of resolving disease-associated changes at scale. To this end, we generated large plasma proteomic profiles across 2,100 individuals spanning six IMIDs and healthy controls, quantifying 7,288 proteins. This enabled joint evaluation of disease associations and genetic regulation through cis and trans protein quantitative trait loci (pQTLs). While most regulatory effects were shared across diseases, a focused set of disease-specific signals revealed distinctive and, in several cases, previously uncharacterized pathways of pathogenic relevance, refining our view of both common and divergent IMID mechanisms. We then integrated these pQTLs with large public proteogenomic resources to derive a score that prioritizes proteins supported by genetic evidence consistent with a causal role in IMID risk. These scores showed strong enrichment for targets of approved therapies and their first-degree interactors across all six diseases, indicating that they capture biologically and therapeutically meaningful mechanisms. Incorporating blood eQTL information enabled direct comparison between protein- and transcript-level evidence, and a combined multi-layer score improved prioritization over either modality alone. Although the two molecular layers showed partial overlap, they contributed largely non-redundant information, highlighting complementary aspects of immune dysregulation and broadening the set of genetically supported targets. This study provides an integrated molecular view of shared and disease-specific processes across IMIDs and introduces a scalable approach for identifying genetically supported therapeutic targets using complementary proteomic and transcriptomic evidence.