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Clinical Trial
. 2013 Mar 19;110(12):4673-8.
doi: 10.1073/pnas.1217238110. Epub 2013 Mar 4.

Identification of genetic variants influencing the human plasma proteome

Affiliations
Clinical Trial

Identification of genetic variants influencing the human plasma proteome

Åsa Johansson et al. Proc Natl Acad Sci U S A. .

Abstract

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.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Heritability of peptide abundance levels. Histogram of estimated heritabilities for all peptides. The dark green indicates significant observations (FDR P value <0.05).
Fig. 2.
Fig. 2.
Gene structure and location of the identified and quantified peptides. (A) Peptides in HPT and the association between rs217184 and each peptide. (B) Peptides in ATA1 and the association between three different SNPs (rs1243165, rs709932, and rs17090693) and each peptide.
Fig. 3.
Fig. 3.
Heatmap of pairwise correlation coefficients between HPT peptides. Each point in the heatmap represents the correlation coefficient between two peptides ranging from R = −0.5 (white) to R = 1 (red). (Upper) Effect of rs217184 on the abundance level of each peptide is illustrated. Each peptide is represented by the effect (beta) and the 95% confidence interval (CI) of the effect. The minor allele in rs217184 is associated with increased abundance levels for 15 peptides (P value nominal <0.05) and with decreased abundance levels for one peptide. Observations where the CI does not include zero represent nominally significant observations (P < 0.05). The color histogram (Upper Right) shows the distribution of correlation coefficients.

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