Plasma proteome analyses in individuals of European and African ancestry identifycis-pQTLs and models for proteome-wide association studies

Abstract

Improved understanding of the genetic architecture of the proteome through studies of larger sample size, ethnic diversity, and advanced methods can facilitate the identification of causal mechanisms for complex traits. We conducted a comprehensive analysis of the common variant cis-regulatory genetic architecture of 4,665 plasma proteins or protein complexes ascertained using an aptamer-based technology from 7,213 European Americans (EA) and 1,871 African Americans (AA) from the Atherosclerosis Risk in Communities (ARIC) cohort study. We identified and fine-mapped 1,992 plasma proteins or protein complexes in EA and 1,605 in AA, with majority overlapping in EA, which had at least one significant single-nucleotide polymorphism (SNP) in cis region. Estimates of cis-heritability (cis-h2) for plasma proteins were similar across the two ethnic groups (median cis-h2 = 0.09 for EA and 0.10 for AA). Elastic-net based models for cis-SNP-based protein prediction produced high accuracy for the EA population (median R2/cis-h2=0.79), and notably for the AA (median R2/cis-h2 = 0.69), despite the much smaller sample size in the latter population. We illustrate the application of these models to conduct proteome-wide association studies (PWAS) for two related complex traits, serum urate and gout, and further conduct conditional analyses to interpret findings in the context of those from transcriptome-wide association studies (TWAS).

Genetic analysis of blood molecular phenotypes reveals regulatory networks affecting complex traits: a DIRECT study

“…In conclusion, we estimated a large proportion of shared genetic regulation across gene expression and proteins. However, as reported by others before 5,16–18,22,23 , the genetic regulation of circulating proteins seems to involve additional protein specific regulatory processes that complicates the identification of genomic regions acting in both phenotypes.…”

“…In summary, our results support previous reports of abundant pleiotropic effects on cis-eQTLs 14 with limited information for cis-pQTLs. Given the increased number of proteins and samples evaluated in pQTL studies and reports of overlapping genetic architecture properties with gene expression [16][17][18] , we expect these pleiotropic effects to be also abundant at the protein level.…”

Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseases

“…We estimated the putative causal role of 1,310 proteins on eight diseases in the NFE samples using proteome-wide association study (PWMR) and sensitivity analyses. For the exposure of the analysis, 5,418 conditional independent pQTLs of 1,310 proteins in European samples from ARIC (Zhang et al, 2021) were selected as genetic predictors. For outcomes, eight of the 14 diseases from GBMI were selected since they had full GWAS summary statistics in both European and African ancestries and had relatively good sample size (> 100 cases).…”

Proteome-wide Mendelian randomization in global biobank meta-analysis reveals multi-ancestry drug targets for common diseases

“…Cis-acting pQTLs within 500KB of the protein-coding gene were selected as genetic instruments for the proteome MR analyses, since cis-acting pQTLs are more likely to have protein-specific effects than trans-acting pQTLs 4 . For the discovery MR analysis, 6,144 conditionally independent pQTLs of 1,310 proteins in 7,213 Europeans (Table S1) and 3,875 conditionally independent pQTLs of 1,311 proteins in 1,871 Africans (Table S2) derived from the Atherosclerosis Risk in Communities Study (ARIC) study 20 were selected as candidate genetic instruments for their respective proteins, where the conditional independent pQTLs were identified using the fine mapping method SuSiE 25 . To increase reliability and boost power, we developed a three-step instrument validation pipeline to filter the pQTLs that best fit the MR assumptions.…”

“…A recent large-scale plasma proteome GWAS study has identified pQTLs in both European and African ancestries and compared the genetic architecture of the proteome across ancestries 20 . This study further estimated the associations of proteins on plasma urate and gout in Europeans using a previously-described transcriptome-wide association study pipeline 21 .…”