Protein quantitative trait locus analysis in African American and non-Hispanic White individuals - Cai, Yanwei; Johnson, Mari; Haessler, Jeffrey; Molstad, Aaron J.; Hwang, Shih-Jen; Joehanes, Roby; Murabito, Joanne M.; Tahir, Usman A.; Franceschini, Nora; Gerszten, Robert E.; Sun, Wei; Levy, Daniel; et al. (Genome Biology, 2025)
Background Substantial efforts have been dedicated to exploring the link between genetic regulation and the proteome, informing studies of complex trait mechanisms. Most of these efforts have been limited to populations of European ancestry. Results We conduct an Olink protein quantitative trait locus (pQTL) analysis on 1245 proteins involving 1033 self-identified African American (AA) and 1764 non-Hispanic White (NHW) participants from the Women’s Health Initiative and Framingham Heart Study. For replication of candidate pQTLs, we use data from 534 self-identified AA adults from the Jackson Heart Study and protein genome-wide association analysis statistics from the UK Biobank Pharma Proteomics Project, including 54,219 participants, of whom 931 are of African ancestry. In total, we identify and validate 5103 pQTLs (4496 or 88% cis- and 602 or 12% trans-pQTLs) for 983 proteins. Among these, 195 are previously unreported, with most (166 or 85%) identified in our AA sample, many of which were essentially monomorphic in European reference populations. Several of these newly identified African ancestry-specific pQTLs have been reported in ClinVar; our results suggest impact on circulating protein levels, potentially bolstering evidence for clinical significance. We identify a “cis pQTL hotspot” within the leukocyte receptor gene cluster on human chromosome 19q13.4. We also provide examples where a particular cis-pQTL, identified through conditional analysis, offers biological insights into an overlapping GWAS signal for disease susceptibility. Conclusions The identification of previously undescribed African ancestry-specific pQTLs contributes to understanding protein genetic regulation and highlights the significance of proteomic analysis in diverse populations.