Venous thromboembolism occurs frequently in cancer patients. Two variants in the factor 5 gene (F5), rs6025 encoding for the factor V Leiden mutation R506Q, and rs4524 encoding K858R, have been found to be associated with venous thromboembolism. We assessed the joint effect of active cancer and these two F5 variants on venous thromboembolism risk in a case-cohort study. Cases with a first venous thromboembolism (n=609) and a randomly selected age-weighted cohort (n=1,691) were sampled from the general population in Tromsø, Norway. Venous thromboembolism was classified as cancer-related if it occurred in the period 6 months before to 2 years after a diagnosis of cancer. Active cancer was associated with an 8.9-fold higher risk of venous thromboembolism (95% CI 7.2-10.9). The risk of cancer-related venous thromboembolism was 16.7-fold (95% CI 9.9-28.0) higher in subjects heterozygous for rs6025 compared with non-carriers of this variant without active cancer. In subjects with active cancer the risk of venous thromboembolism was 15.9-fold higher (95% CI 9.1-27.9) in those with one risk allele at rs4524, and 21.1-fold (95% CI 12.4-35.8) higher in those with two risk alleles compared with non-carriers without active cancer. A synergistic interaction was observed between active cancer and factor V Leiden (relative excess risk due to interaction 7.0; 95% CI 0.5-14.4) and rs4524 (relative excess risk due to interaction 15.0; 95% CI 7.5-29.2). The incidence of venous thromboembolism during the initial 6 months following a diagnosis of cancer was particularly high in subjects with risk alleles at these loci. This implies that the combination of cancer and F5 variants synergistically increases venous thromboembolism risk.

Background

Identifying genetic variation associated with plasma protein levels, and the mechanisms by which they act, could provide insight into alterable processes involved in regulation of protein levels. Although protein levels can be affected by genetic variants, their estimation can also be biased by missense variants in coding exons causing technical artifacts. Integrating genome sequence genotype data with mass spectrometry-based protein level estimation could reduce bias, thereby improving detection of variation that affects RNA or protein metabolism.

Methods

Here, we integrate the blood plasma protein levels of 664 proteins from 165 participants of the Tromsø Study, measured via tandem mass tag mass spectrometry, with whole-exome sequencing data to identify common and rare genetic variation associated with peptide and protein levels (protein quantitative trait loci [pQTLs]). We additionally use literature and database searches to prioritize putative functional variants for each pQTL.

Results

We identify 109 independent associations (36 protein and 73 peptide) and use genotype data to exclude 49 (4 protein and 45 peptide) as technical artifacts. We describe 2 particular cases of rare variation: 1 associated with the complement pathway and 1 with platelet degranulation. We identify putative functional variants and show that pQTLs act through diverse molecular mechanisms that affect both RNA and protein metabolism.

Conclusions

We show that although the majority of pQTLs exert their effects by modulating RNA metabolism, many affect protein levels directly. Our work demonstrates the extent by which pQTL studies are affected by technical artifacts and highlights how prioritizing the functional variant in pQTL studies can lead to insights into the molecular steps by which a protein may be regulated.