Genome-wide Association Study Of Plasma Proteins Identifies Putatively Causal Genes, Proteins, And Pathways For Cardiovascular Disease

Abstract

Summary:Identifying genetic variants associated with circulating protein concentrations (pQTLs) and integrating them with variants from genome-wide association studies (GWAS) may illuminate the proteome's causal role in disease and bridge a GWAS knowledge gap for hitherto unexplained SNP-disease associations. We conducted GWAS of 71 high-value proteins for cardiovascular disease in 6,861 Framingham Heart Study participants followed by external replication. We comprehensively mapped thousands of pQTLs, including functional annotations and clinical-trait associations, and created an integrated plasma-protein-QTL searchable database. We next identified 15 proteins with pQTLs coinciding with coronary heart disease (CHD)-related variants from GWAS or tested causal for CHD by Mendelian randomization; most of these proteins were associated with new-onset cardiovascular disease events in Framingham participants with long-term follow-up. Identifying pQTLs and integrating them with GWAS results yields insights into genes, proteins, and pathways that may be causally associated with disease and can serve as therapeutic targets for treatment and prevention.

Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases

“…Figure 1A summarises the genetic instrument selection and validation process, with expanded detail in Supplementary Figure 1. We curated 3606 SNPs associated with 2656 proteins from five studies 12 13 14 15 16 . After removing proteins and SNPs in the major histocompatibility complex (MHC) region and performing strict LD clumping we retained 2113 pQTLs associated with 1699 proteins (Online Method: Instruments selection ; instruments listed in Supplementary Table 1).…”

“…pQTLs from five GWAS (Sun et al , Emilsson et al , Suhre et al , Folkersen et al and Yao et al ) 12 13 14 15 16 were used as genetic instruments to estimate the causal effect of plasma protein levels on human diseases and other phenotypes (Supplementary Figure 1).…”

“…Plasma proteins play key roles in a range of biological processes, are frequently dysregulated in disease, and represent a major source of druggable targets 9 10 11 . Recently published genome-wide association studies (GWAS) of plasma protein levels have identified 3606 conditionally independent single nucleotide polymorphisms (SNPs) associated with 2656 proteins (‘protein quantitative trait loci’, pQTLs) in more than 1000 participants 12 13 14 15 16 .While conventional randomized controlled trials are time-consuming and costly, these genetic associations offer the potential to systematically test the causal effects of a large number of potential drug targets on the human disease phenome through Mendelian randomization (MR) 17 . In essence, MR exploits the random allocation of genetic variants at conception and their associations with disease risk factors to uncover causal relationships between human phenotypes 18 , and has been described in detail previously 19 20 .…”

Big knowledge from big data in functional genomics

“…in log-transformed values [23]. The applicability of Mendelian randomisation has been substantially broadened by exploiting DNA variants that predict RNA [24,25] and protein [26,27] levels to test for a causal effect on traits or disease risk. While challenges need to be overcome, most specifically that of horizontal pleiotropy [28], Mendelian randomisation has potential to reveal causal relationships between DNA variant and trait, and between trait pairs [29].…”