Large Bi-ethnic Study of Plasma Proteome Leads to Comprehensive Mapping of cis-pQTL and Models for Proteome-wide Association Studies

• Published in: bioRxiv
• Main Authors: Zhang, Jingning, Dutta, Diptavo, Köttgen, Anna, Tin, Adrienne, Schlosser, Pascal, Grams, Morgan E, Harvey, Benjamin, Consortium, Ckdgen, Yu, Bing, Boerwinkle, Eric, Coresh, Joseph, Chatterjee, Nilanjan
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 06.10.2021
• Subjects: Aptamers; Arteriosclerosis; Gene expression; Gene mapping; Gene polymorphism; Gout; Heritability; Minority & ethnic groups; Plasma; Plasma proteins; Proteins; Proteomes; Single-nucleotide polymorphism; Transcriptomes; Uric acid
• DOI: 10.1101/2021.03.15.435533

Improved understanding of genetic regulation of proteome can facilitate the identification of causal mechanisms for complex traits. We analyzed data on 4,657 plasma proteins from 7,213 European American (EA) and 1,871 African American individuals from the ARIC study, and further replicated findings on 467 AA individuals from the AASK study. We identified 2,004 plasma proteins in EA and 1,618 in AA, with majority overlapping, which showed significant genetic associations with common variants in cis-regions. Availability of AA sample led to smaller credible sets and identification of a significant number of population-specific cis-pQTLs. Estimates of cis-heritability for proteins were similar across EA and AA (median cis-h2=0.09 for EA and 0.10 for AA) and tended to be lower than those of gene expressions. Elastic-net-based algorithms produced high accuracy for protein prediction in each population, but models developed in AA were more transportable to EA than conversely. An illustrative application of proteome-wide association studies (PWAS) to serum urate and gout, implicated several proteins, including IL1RN, revealing the promise of the drug anakinra to treat acute gout flares. Our study demonstrates the value of large and diverse ancestry study for understanding genetic mechanisms of molecular phenotypes and their relationship with complex traits. Competing Interest Statement Proteomic assays in ARIC were conducted free of charge as part of a data exchange agreement with Soma Logic. Footnotes * Major revisions include (1) Unifying definition of the cis region to be +/-500Kb in both pQTL and PWAS analyses. (2) Addition of data from a second African American (AA) Study for carrying out replication. The analysis shows a high replication rate (>90% concordance rate for the direction of effect-estimates and 70% detected to be statistically significant at a stringent multiple testing adjusted threshold) of our original findings from the ARIC AA population. (3) Cataloging of AA-specific pQTLs which are non-existent or extremely rare in European American (EA) population. In fact, we found 30% of the cis-pQTLs detected in the AA population were population-specific. (4) Cataloging of pQTLs which may be influenced by potential epitope effects associated with protein-altering variants and carrying out downstream sensitivity analysis. (5) Large-scale pQTL-eQTL colocalization analyses across all GTEX tissue. (6) Providing estimation of effect sizes and confidence intervals associated with PWAS and TWAS findings. Validating the top gene-tissue combination identified through TWAS models in V7 using preliminary models that were available to us based on V8.  (7) A systematic connection of all cis-heritable proteins to active drug candidates is provided as an additional resource. (8) We have now released the full summary stat for a total of 4,657 proteins analyzed in our paper to our website http://nilanjanchatterjeelab.org/pwas/ Manuscript, supplemental figures, and tables were mainly revised based on those eight points. * http://nilanjanchatterjeelab.org/pwas/