To identify genetic variants that have a regulatory impact on circulating microRNAs (miRNAs) and to connect genetic risk to blood traits/biomarkers through the circulating miRNAs. Leveraging miRNA-Seq data and the 1000 Genomes imputed genotypes, we carried out genome-wide association analysis for SNPs that regulate the expression of circulating miRNAs in a sample of 710 unrelated subjects of European ancestry. Wherever possible, we used data from the Framingham and the Geuvadis studies to replicate our findings. We found at least one genome-wide significant (P < 5e-8) miRNA-eQTL (mirQTL) for 143 circulating miRNAs. Overall each mirQTL explained a small portion (<1%) of variation in miRNA levels; however, we identified a few mirQTLs that explained 4% to 20% of variation in miRNA levels in plasma. Unlike trans-mirQTLs (P = 0.7), cis-mirQTLs tend to be also associated with their counterpart mature miRNAs (P < 0.0001), this suggests trans-mirQTLs exert their effect through processes that affect the stability of mature miRNAs; whereas, cis-mirQTLs mainly regulate the expression of primary-miRNAs. Next, we used the identified mirQTLs to investigate the links between circulating miRNAs with blood traits/biomarkers through Mendelian randomization analysis. We found miR-1908-5p plays an important role in regulating low-density lipoprotein (LDL), total cholesterol (TC), fasting glucose, HbA1c, and several lipid-metabolites in blood, whereas, miR-10b-5p mediates the trans-regulatory effect of the ABO locus on several blood proteins, coronary artery disease, and TC. Moreover, we demonstrated that a higher plasma level of miR-199a is causally associated with lower levels of LDL and TC. Finally, we found miR-143-3p and miR-145-5p are functionally related and mediate the effect of ZFPM2 on a number of its protein targets in blood including VEGFA, SERPINE1, and PDGFs. This study identifies SNPs that have a regulatory impact on circulating miRNAs, and underlines the role of several circulating miRNAs in mediating the effect of a number of GWAS loci on cardiometabolic phenotypes.