Identification of genetic variants influencing the human plasma proteome.

Johansson Å, Enroth S, Palmblad M, Deelder AM, Bergquist J, Gyllensten U

Proc. Natl. Acad. Sci. U.S.A. 110 (12) 4673-4678 [2013-03-19; online 2013-03-15]

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 high-resolution mass spectrometry (MS) with genome-wide SNP data. We identified and quantified the abundance of 1,056 tryptic-digested 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 ε4 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.

NGI Uppsala (SNP&SEQ Technology Platform)

National Genomics Infrastructure

PubMed 23487758

DOI 10.1073/pnas.1217238110

Crossref 10.1073/pnas.1217238110

pii: 1217238110
pmc: PMC3606982


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