Improved understanding of the proteome can facilitate the identification of causal mechanisms for complex traits. We conducted a comprehensive analysis of the common variant cis-regulatory genetic architecture of 4,665 plasma proteins from 7,213 European Americans (EA) and 1,871 African Americans (AA) from the Atherosclerosis Risk in Communities (ARIC) cohort study. We identified and fine-mapped 1,992 plasma proteins in EA and 1,605 in AA, which had significant cis- single-nucleotide polymorphism (SNP) associations. Estimates of cis-heritability (cis-h2) for plasma proteins were similar across EA and AA (median cis-h2 = 0.09 for EA and 0.10 for AA). Elastic-net-based models for cis-SNP-based protein prediction produced high accuracy (median R2/cis-h2 = 0.79 for EA and 0.69 for AA). We illustrate the application of these models to conduct proteome-wide association studies (PWAS) for two related complex traits, serum urate and gout, and further conduct conditional analyses to interpret findings in the context of those from transcriptome-wide association studies (TWAS).