Genetic variants influencing the transcriptome have been extensively studied. However, the impact of the genetic factors on the human proteome is largely unexplored, mainly due to lack of suitable high-throughput methods. Here we present unique and comprehensive identification of genetic variants affecting the human plasma protein profile by combining high-throughput and highresolution mass spectrometry (MS) with genome-wide SNP data. We identified and quantified the abundance of 1,056 trypticdigested peptides, representing 163 proteins in the plasma of 1,060 individuals from two population-based cohorts. The abundance level of almost one-fifth (19%) of the peptides was found to be heritable, with heritability ranging from 0.08 to 0.43. The levels of 60 peptides from 25 proteins, 15% of the proteins studied, were influenced by cis-acting SNPs. We identified and replicated individual cis-acting SNPs (combined P value ranging from 3.1 × 10 −52 to 2.9 × 10 −12 ) influencing 11 peptides from 5 individual proteins. These SNPs represent both regulatory SNPs and nonsynonymous changes defining well-studied disease alleles such as the e4 allele of apolipoprotein E (APOE), which has been shown to increase risk of Alzheimer's disease. Our results show that high-throughput mass spectrometry represents a promising method for large-scale characterization of the human proteome, allowing for both quantification and sequencing of individual proteins. Abundance and peptide composition of a protein plays an important role in the etiology, diagnosis, and treatment of a number of diseases. A better understanding of the genetic impact on the plasma proteome is therefore important for evaluating potential biomarkers and therapeutic agents for common diseases.protein quantitative trait loci | population proteomics O ur understanding of the impact of genetic variation on human traits has been greatly advanced using high-throughput SNP genotyping and massively parallel sequencing. The large number of genome-wide association studies (GWAS) performed have resulted in the identification of hundreds of SNPs that are associated with human traits and diseases (1, 2). The functional impact of most of the SNPs influencing human traits has not been well characterized. Whereas nonsynonymous SNPs affect the amino acid sequence directly and could alter the function of the resulting protein, other SNPs may have an impact on splice sites (3) or influence amount or stability of the mRNA (4). GWAS studies relating the genetic variability to the transcript profile have identified a number of cis-regulatory SNPs affecting expression quantitative traits (eQTs) (5, 6). Evidently, the expression of many genes is influenced by a nearby SNP, with cis-regulatory SNPs being overrepresented among SNPs associated with human phenotypes (1). Studies have also addressed the impact of genetic variability on levels of endogenous metabolites, such as sugars, biogenic amines, acylcarnitines, and glycerophospho-and sphingolipids, which can be measured in either human urin...