Identification of genetic variants influencing the human plasma proteome
2013 (English)In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 110, no 12, 4673-4678 p.Article in journal (Refereed) Published
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 x 10(-52) to 2.9 x 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 epsilon 4 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.
Place, publisher, year, edition, pages
2013. Vol. 110, no 12, 4673-4678 p.
protein quantitative trait loci, population proteomics
IdentifiersURN: urn:nbn:se:uu:diva-200115DOI: 10.1073/pnas.1217238110ISI: 000317521600059OAI: oai:DiVA.org:uu-200115DiVA: diva2:622623