Proteogenomic analysis integrated with electronic health records data reveals disease-associated variants in Black Americans
Usman A. Tahir, … , Laura M. Raffield, Robert E. Gerszten
Usman A. Tahir, … , Laura M. Raffield, Robert E. Gerszten
Published September 24, 2024
Citation Information: J Clin Invest. 2024;134(21):e181802. https://doi.org/10.1172/JCI181802.
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Clinical Research and Public Health Genetics Immunology

Proteogenomic analysis integrated with electronic health records data reveals disease-associated variants in Black Americans

Abstract

BACKGROUND Most GWAS of plasma proteomics have focused on White individuals of European ancestry, limiting biological insight from other ancestry-enriched protein quantitative loci (pQTL).METHODS We conducted a discovery GWAS of approximately 3,000 plasma proteins measured by the antibody-based Olink platform in 1,054 Black adults from the Jackson Heart Study (JHS) and validated our findings in the Multi-Ethnic Study of Atherosclerosis (MESA). The genetic architecture of identified pQTLs was further explored through fine mapping and admixture association analysis. Finally, using our pQTL findings, we performed a phenome-wide association study (PheWAS) across 2 large multiethnic electronic health record (EHR) systems in All of Us and BioMe.RESULTS We identified 1,002 pQTLs for 925 protein assays. Fine mapping and admixture analyses suggested allelic heterogeneity of the plasma proteome across diverse populations. We identified associations for variants enriched in African ancestry, many in diseases that lack precise biomarkers, including cis-pQTLs for cathepsin L (CTSL) and Siglec-9, which were linked with sarcoidosis and non-Hodgkin’s lymphoma, respectively. We found concordant associations across clinical diagnoses and laboratory measurements, elucidating disease pathways, including a cis-pQTL associated with circulating CD58, WBC count, and multiple sclerosis.CONCLUSIONS Our findings emphasize the value of leveraging diverse populations to enhance biological insights from proteomics GWAS, and we have made this resource readily available as an interactive web portal.FUNDING NIH K08 HL161445-01A1; 5T32HL160522-03; HHSN268201600034I; HL133870.

Authors

Usman A. Tahir, Jacob L. Barber, Daniel E. Cruz, Meltem Ece Kars, Shuliang Deng, Bjoernar Tuftin, Madeline G. Gillman, Mark D. Benson, Jeremy M. Robbins, Zsu-Zsu Chen, Prashant Rao, Daniel H. Katz, Laurie Farrell, Tamar Sofer, Michael E. Hall, Lynette Ekunwe, Russell P. Tracy, Peter Durda, Kent D. Taylor, Yongmei Liu, W. Craig Johnson, Xiuqing Guo, Yii-Der Ida Chen, Ani W. Manichaikul, Deepti Jain, NHLBI Trans-Omics for Precision Medicine Consortium, Thomas J. Wang, Alex P. Reiner, Pradeep Natarajan, Yuval Itan, Stephen S. Rich, Jerome I. Rotter, James G. Wilson, Laura M. Raffield, Robert E. Gerszten

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