Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease

Abstract

Recent advances in highly multiplexed immunoassays have allowed systematic large-scale measurement of hundreds of plasma proteins in large cohort studies. In combination with genotyping, such studies offer the prospect to 1) identify mechanisms involved with regulation of protein expression in plasma, and 2) determine whether the plasma proteins are likely to be causally implicated in disease. We report here the results of genome-wide association (GWA) studies of 83 proteins considered relevant to cardiovascular disease (CVD), measured in 3,394 individuals with multiple CVD risk factors. We identified 79 genome-wide significant (p<5e-8) association signals, 55 of which replicated at P<0.0007 in separate validation studies (n = 2,639 individuals). Using automated text mining, manual curation, and network-based methods incorporating information on expression quantitative trait loci (eQTL), we propose plausible causal mechanisms for 25 trans-acting loci, including a potential post-translational regulation of stem cell factor by matrix metalloproteinase 9 and receptor-ligand pairs such as RANK-RANK ligand. Using public GWA study data, we further evaluate all 79 loci for their causal effect on coronary artery disease, and highlight several potentially causal associations. Overall, a majority of the plasma proteins studied showed evidence of regulation at the genetic level. Our results enable future studies of the causal architecture of human disease, which in turn should aid discovery of new drug targets.

Fig 1. Genome-wide association strength of all measured plasma proteins.

The extent of each stack indicates the negative log P of association between the plasma protein and SNPs. Stacks with black dots and black text labels indicate cis-associations. Stacks with hollow circles and grey text labels indicate trans-associations; their targets are indicated with central colour coded lines. Consequently, plasma proteins having both cis- and trans-effects can be identified as those with a black dot stack as well as connecting lines from hollow dots, e.g. XPNPEP2 or CCL4. Fully drawn circle shows P = 5e-8. Dashed circle shows 1e-15. A detailed table of the genome-wide significant associations in this figure is available as supplemental S1 Table. A zoomable and interactive version of this figure is available at www.olink-improve.com.

Fig 2. String-database network connections between proximal cis-gene and target plasma protein.

All short String paths that connect proximal cis-genes with the target plasma protein are shown. The colour intensity of each gene shows the eQTL association-strength with the index-SNP. The nodes highlighted with bold border show paths that satisfy P<0.05 in network permutation analysis. A) the rs61598054-SNP is harboured in an intron of the LACE1 gene, but have no paths to the target gene NGF and a more likely mechanism is therefore FOXO3 -> AKT1 -> NGF, which involves a rs61598054-trans-eQTL effect on AKT1. In permutation analysis of re-wired networks this is stronger than 95% of random networks. B) Similarly for rs693918, while located between SRD5A2 and MEMO1, the path XDH -> TLR4 -> IL18 is a more likely mechanistic path, supported by eQTL effects on both XDH and TLR4. C) The rs61598054-AKT1 trans-eQTL from panel A in 235 IFN-stimulated monocytes and the rs10947260-ATF3 trans-eQTL from panel D in 89 mammary artery samples. D) Example of ambiguous findings regarding the rs10947260 -> -> -> IL6: The SNP has a coding-proxy in BTNL2, literature mining evidence for the AGER gene, but also eQTL-weighted pathway evidence for both ATF6B and NOTCH4.