There is a pressing need to identify novel biomarkers and therapeutic targets to address the epidemiological burden of coronary artery disease (CAD). Mendelian Randomization analysis (MR) leverages Genome-Wide Association Study (GWAS) data to infer the causal mechanism underlying the phenotype of interest. The proteome is the central mediator of the etiology and pathophysiology of multifactorial diseases such as CAD. Here, we screened for potential biomarkers and therapeutic targets for CAD through MR by using genetically predicted levels of plasma proteome followed by immune cell traits and transcriptomic analysis. The main workflow of our study is outlined in Figure 1. Briefly, MR analysis was performed with protein quantitative trait loci (pQTL) and meta-analysis of four independent GWASs. Sensitivity analysis was performed to ensure the robustness of identified proteins. Pathway Enrichment analysis on whole-blood transcriptome was performed with GSEA. Secondary MR explored the causal effect of 731 immune cell traits on CAD risk. In total, 11 overlapping candidate proteins (P<0.05, OR>1.0) were identified from the plasma proteome meta-analysis, including LPA, PLA2G7, and PCSK9, substantiating the validity of our MR analysis. Functional annotation of candidate proteins identified LCAT and CA11 as promising therapeutic targets and biomarkers. LCAT suppression is protective against atherosclerosis in mice models, while the functional significance of CA11 remains to be elucidated. Transcriptomic analysis shows enrichment in IL-2 signaling pathways reflective of the exhaustion of CD28 on cytotoxic T cells identified via secondary MR using immune-cell traits. Together, these results are indicative of immunosenescence as a risk factor for CAD. Overall, our results revealed that an altered immune landscape increased the risk for CAD and unraveled an encouraging avenue for early diagnosis and treatment of CAD.