Cross-ancestry comparison of aptamer and antibody protein measures
Nature Communications, 2026
Nicholas J., Katz D., Tahir U., Debban C., Aguet F., Blackwell T., Bowler R., Broadaway K., Chen J., Clish C., Coresh J., Cornell E., Cruz D., Deo R., Doyle M., Durda P., Ekunwe L., Floyd J., Gill D., Guo X., Hoogeveen R., Johnson C., Lange L., Li Y., Manning A., Meigs J., Mi M., Mychaleckyj J., Olson N., Pratte K., Psaty B., Reiner A., Ruan P., Sevilla-Gonzalez M., Shah A., Sun Q., Tracy R., Wen J., Wood A., Wilson J., Young K., Yu B., Rooney M., Manichaikul A., Dubin R., Mohlke K., Rich S., Rotter J., Ganz P., Gerszten R., Taylor K., Raffield L.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Wider Proteomics Studies | Technology Evaluation | Plasma |  Olink Explore 3072/384 |
Abstract
Measures from affinity-proteomics platforms often correlate poorly, challenging interpretation of protein associations with genetic variants and phenotypes. Here, we examine 2157 proteins measured on both SomaScan 7k and Olink Explore 3072 across 1930 participants with genetic similarity to European, African, East Asian, and Admixed American ancestry references. Inter-platform correlation coefficients for these 2157 proteins follow a bimodal distribution (median r = 0.30). We evaluate protein measure associations with genetic variants, and find approximately 25-30% of the signals on each platform are likely driven by protein-altering variants. We highlight 80 proteins that correlate differently across ancestry groups likely in part due to differing protein-altering variant frequencies by ancestry. Furthermore, adjustment for protein-altering variants with opposite directions of effect by platform improves inter-platform protein measure correlation and results in more concordant genetic and phenotypic associations. Hence, protein-altering variants need to be accounted for across ancestries to facilitate platform-concordant and accurate protein measurement.